Search is not available for this dataset
query
stringlengths 1
13.4k
| pos
stringlengths 1
61k
| neg
stringlengths 1
63.9k
| query_lang
stringclasses 147
values | __index_level_0__
int64 0
3.11M
|
|---|---|---|---|---|
Alpha-anonymization techniques for privacy preservation in social networks | Towards identity anonymization on graphs | Face recognition: A literature survey | eng_Latn | 17,900 |
Security and Privacy in Smart City Applications: Challenges and Solutions | The pursuit of citizens' privacy: a privacy-aware smart city is possible | Optimizing Quantiles in Preference-based Markov Decision Processes | eng_Latn | 17,901 |
Measuring self-disclosure online: Blurring and non-response to sensitive items in web-based surveys | Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking | Towards segment-based recognition of argumentation structure in short texts | eng_Latn | 17,902 |
Correlated network data publication via differential privacy | Quad trees a data structure for retrieval on composite keys | Randomizing Social Networks: a Spectrum Preserving Approach | eng_Latn | 17,903 |
security and privacy for mobile healthcare networks : from a quality of protection perspective . | Privacy-Preserving ECG Classification With Branching Programs and Neural Networks | Identification of Cognates and Recurrent Sound Correspondences in Word Lists | eng_Latn | 17,904 |
Privacy-Preserving User-Auditable Pseudonym Systems | Distributed privacy-preserving transparency logging | Identification of a pathway for intelligible speech in the left temporal lobe. | eng_Latn | 17,905 |
Preserving differential privacy in convolutional deep belief networks | Differential privacy and robust statistics | A Cost-Effective Framework for Preference Elicitation and Aggregation | eng_Latn | 17,906 |
A Survey on Privacy Preserving Data Mining Techniques | A Survey: Privacy Preservation Techniques in Data Mining | Aspirin or Rivaroxaban for VTE Prophylaxis after Hip or Knee Arthroplasty | kor_Hang | 17,907 |
Using randomized response techniques for privacy-preserving data mining | Beyond Concern: Understanding Net Users' Attitudes About Online Privacy | Uterine activity during the third stage of labor. | eng_Latn | 17,908 |
Structure Based Data De-Anonymization of Social Networks and Mobility Traces | Robust De-anonymization of Large Sparse Datasets | Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway | eng_Latn | 17,909 |
The Pitfalls of Hashing for Privacy | anonymity , unobservability , and pseudonymity - a proposal for terminology . | Learning Activity Progression in LSTMs for Activity Detection and Early Detection | eng_Latn | 17,910 |
The Capacity of Private Information Retrieval From Coded Databases | A Survey on Network Codes for Distributed Storage | A scalable system for real-time control of dexterous surgical robots | kor_Hang | 17,911 |
Privacy in Recommender Systems | Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions | Enhanced memory ability: Insights from synaesthesia | eng_Latn | 17,912 |
LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks | Differential privacy: A survey of results | Multicell converters: active control and observation of flying-capacitor voltages | eng_Latn | 17,913 |
mobile crowdsensing : current state and future challenges . | Privacy Preserving Data Mining | SMART 6: recent updates and new developments | eng_Latn | 17,914 |
( alpha , k ) - anonymity : an enhanced k - anonymity model for privacy preserving data publishing . | Association rule hiding | High resolution image formation from low resolution frames using Delaunay triangulation | eng_Latn | 17,915 |
Crowdsourcing-based evaluation of privacy in HDR images | Framework for objective evaluation of privacy filters | The memory effect and its implications on Web QoE modeling | yue_Hant | 17,916 |
Differentially private frequent subgraph mining | Calibrating Noise to Sensitivity in Private Data Analysis | Pyramid Attention Network for Semantic Segmentation | eng_Latn | 17,917 |
Effective Social Graph Deanonymization Based on Graph Structure and Descriptive Information | Preserving Privacy in Social Networks Against Neighborhood Attacks | OLED Defect Inspection System Development through Independent Component Analysis | eng_Latn | 17,918 |
A theory of term weighting based on exploratory data analysis | Inferring probability of relevance using the method of logistic regression | Privacy Preserving Social Network Data Publication | eng_Latn | 17,919 |
Internet of Vehicles and Autonomous Connected Car - Privacy and Security Issues | A learning theory approach to non-interactive database privacy | An Efficient Parallel Implementation for Three-Dimensional Incompressible Pipe Flow Based on SIMPLE | eng_Latn | 17,920 |
writer profiling without the writer ' s text . | Linguistic Style Matching In Social Interaction | algebraic cryptanalysis of the data encryption standard . | eng_Latn | 17,921 |
Privacy-Preserving Crowdsourced Spectrum Sensing | A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing | novel design of intelligent internet - of - vehicles management system based on cloud - computing and internet - of - things . | eng_Latn | 17,922 |
Mapping the structure of semantic memory | Emergence of scaling in random networks | Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo | eng_Latn | 17,923 |
Personality Neuroscience and the Biology of Traits | Genetic and environmental influences on human psychological differences | Plausible Deniability for Privacy-Preserving Data Synthesis | eng_Latn | 17,924 |
An Inconvenient Truth: Algorithmic Transparency & Accountability in Criminal Intelligence Profiling | Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems | Privacy Preserving Data Sharing With Anonymous ID Assignment | eng_Latn | 17,925 |
Privacy-preserving social network publication against friendship attacks | Preserving Privacy in Social Networks Against Neighborhood Attacks | A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks | eng_Latn | 17,926 |
toward practical privacy - preserving analytics for iot and cloud - based healthcare systems . | Differential Privacy | Anonymizing sequential releases | eng_Latn | 17,927 |
Differentially private frequent subgraph mining | Calibrating Noise to Sensitivity in Private Data Analysis | Probabilistic encryption | eng_Latn | 17,928 |
SMC: A Practical Schema for Privacy-Preserved Data Sharing over Distributed Data Streams | Differentially private data release for data mining | Suspended patch antenna with Z-type Strip Plate as broadband impedance transformer | eng_Latn | 17,929 |
Differentially private multidimensional data publishing | Transforming data to satisfy privacy constraints | Robust De-anonymization of Large Sparse Datasets | eng_Latn | 17,930 |
Student Privacy and Educational Data Mining: Perspectives from Industry | More Accurate Student Modeling Through Contextual Estimation of Slip and Guess Probabilities in Bayesian Knowledge Tracing | Smart farming using IOT | eng_Latn | 17,931 |
Differentially private frequent subgraph mining | Differential Privacy | Case records of the Massachusetts General Hospital. Case 30-2005. A 56-year-old man with fever and axillary lymphadenopathy. | eng_Latn | 17,932 |
Evaluating Recommendation Systems | differentially private recommender systems : building privacy into the netflix prize contenders . | Differential privacy: A survey of results | kor_Hang | 17,933 |
Acquisition of linguistic patterns for knowledge-based information extraction | Automatically Constructing a Dictio-nary for Information Extraction Tasks | A Framework for Evaluating Privacy Preserving Data Mining Algorithms* | eng_Latn | 17,934 |
security and privacy for mobile healthcare networks : from a quality of protection perspective . | Privacy-Preserving ECG Classification With Branching Programs and Neural Networks | thermal conductivity of molten materials . is experiment necessary ? . | eng_Latn | 17,935 |
Fairness and transparency in crowdsourcing | Taking a HIT: Designing around Rejection, Mistrust, Risk, and Workers' Experiences in Amazon Mechanical Turk | data mining in education sector : a review . | eng_Latn | 17,936 |
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting | Differential Privacy | The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web] | eng_Latn | 17,937 |
Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries | Differential Privacy | The BellKor 2008 Solution to the Netflix Prize | eng_Latn | 17,938 |
Differential Privacy Preserving Spectral Graph Analysis | Mechanism Design via Differential Privacy | Knowing the occasion of a peaceful death in intensive care units in Thailand | eng_Latn | 17,939 |
Feeling-based location privacy protection for location-based services | Anonysense: privacy-aware people-centric sensing | Entrepreneurship Theory and the Poverty of Historicism Forthcoming , Journal of Management History | eng_Latn | 17,940 |
Decision Tree Classification with Differential Privacy: A Survey | A mathematical theory of communication: Meaning, information, and topology | Application Of Neural Network To Technical Analysis Of Stock Market Prediction | eng_Latn | 17,941 |
A survey of task-oriented crowdsourcing | Predicting protein structures with a multiplayer online game | A standard compliant security framework for IEEE 802.15.4 networks | eng_Latn | 17,942 |
research paper : a globally optimal k - anonymity method for the de - identification of health data . | Incognito: efficient full-domain K-anonymity | Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals | eng_Latn | 17,943 |
Cyber anonymity based on software-defined networking and Onion Routing (SOR) | Blind Signatures for Untraceable Payments | Grading and Classification of Anthracnose Fungal Disease of Fruits based on Statistical Texture Features | eng_Latn | 17,944 |
Explicit B-spline regularization in diffeomorphic image registration | Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain | The role of privacy fatigue in online privacy behavior | eng_Latn | 17,945 |
exploration of efficient symmetric algorithms . | Peformance analysis of data encryption algorithms | Regional Level Influenza Study with Geo-Tagged Twitter Data | eng_Latn | 17,946 |
Public versus Private Blockchains Part 2 : Permissionless Blockchains White | Enigma: Decentralized Computation Platform with Guaranteed Privacy | A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets. | eng_Latn | 17,947 |
Robust Privacy-Preserving Image Sharing over Online Social Networks (OSNs) | Outsource Photo Sharing and Searching for Mobile Devices With Privacy Protection | Classification of Arrhythmia Using Conjunction of Machine Learning Algorithms and ECG Diagnostic Criteria | eng_Latn | 17,948 |
Learning to Estimate the Travel Time | XGBoost: A Scalable Tree Boosting System | Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing | eng_Latn | 17,949 |
Privacy? I Can’t Even! Making a Case for User-Tailored Privacy | What Can Behavioral Economics Teach Us About Privacy? | Convolutional Neural Networks for Steel Surface Defect Detection from Photometric Stereo Images | eng_Latn | 17,950 |
One Method for Provenance Tracking of Product Lifecycle Data in Collaborative Service Environment | It is vital to provides more necessary and accurate data for product services and knowledge discovery through provenance tracking of product lifecycle data. We propose one three-level framework of provenance tracking of product lifecycle data, which is consisting of business level, process level and data level firstly. After the models of product lifecycle data and their data provenance are given, the organization of product lifecycle data and the design of provenance annotations are explored. Then the tracking algorithms are described and one method for product lifecycle data on business level in collaborative service environment is suggested. The method is verified in one prototype system. The verification results show that it is enough to the provenance tracking of product life statuses and physical BOM in collaborative service environment. | Millions of people every day identify many types of popular or widespread items, including interesting entertainment content and malicious network attacks. Unfortunately, much of the information required for these popularity contests has privacy concerns attached to its use. Unless their privacy is preserved, participants may refuse to participate honestly, reducing the quality of the results. Provably ensuring the privacy of participants, while retaining the level of eciency and robustness necessary for a practical protocol, is a serious challenge to privacy-preserving popular item identification. Previous eorts have not obtained the necessary eciency [23] or provide only unproven, heuristic levels of privacy [24, 16, 39, 19]. In this paper, we propose and experimentally evaluate protocols that provably protect the privacy of participants, while adding only a small amount of overhead. | eng_Latn | 17,951 |
Location privacy through anonymous chain in dynamic P2P network | An anonymous chain based privacy protection algorithm was presented to solve the problem of location privacy protecting in dynamic peer-to-peer(P2P) network.Different from the general K-anonymity method,anonymous chain was constructed to break the one-to-one correspondence between the user identity and location information during the forwarding process of query message,and the location privacy was protected with the completion of the query.The algorithm optimizes the selection of intermediate nodes according to the stability of linkage between two nodes in order to deal with the dynamic issues in P2P environment.A connectivity matrix was introduced for the chain constructing algorithm and the security of anonymous chain was proved.A simulation on a real city map for the algorithm showed the effectiveness.The results prove that anonymous chain can be constructed in different density of moving nodes and the optimal intermediate nodes selecting method obviously improves the stability of the chain. | For the purposes of computational dialec- tology or other geographically bound text analysis tasks, texts must be annotated with their or their authors’ location. Many texts are locatable but most ... | eng_Latn | 17,952 |
The value of personal data is the Data Protection and Privacy preliminary condition: synthetic human profiles on the web and ethics | The EU Regulation 2016/679 (GDPR) is a landmark, and we describe the value of personal data as the main starting point to address any possible issue. Once clarified the meaning of that value as a top-level point from which it not possible prescind and the strict relationship with ethics, we present one of the risks, that is the 'synthetic human profile' and can be realised by the use of faces images available on the web. In conclusion, we propose a blockchain system to guarantee the data subjects identity. | In the past, the primary threat to the patient as person was a medical utilitarianism that would sacrifice the individual for the collective, that would coercively (ab)use a person for the sake of an in-group's health or happiness. Today, the threat is not only from vainglorious social groups but also from valorized genes and genomes. An over-valuation of genes risks making persons seem epiphenomenal. A central thesis of this article is that religious healthcare professionals have unique resources to combat this. | eng_Latn | 17,953 |
Privacy Preservation in a Decentralized Calendar System | Privacy perservation, in terms of sensitive data access and management, is an important feature of decentralized calendar systems. Indeed, when users delegate their sensitive data such as timetables to an autonomous agent, this one executes many automatic data processing without their intervention: users lost a part of their data control. To tackle this problem, we propose in this article to extend a concrete application of calendars management multi-agent system by implementing a specific protocol for sensitive data transactions that represents the first step of privacy preservation in multi-agent systems. | This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Discrete and Continuous Dynamical Systems - Series A following peer review. The definitive publisher-authenticated version 2015, 35(3), pp. 1009-1037 is available online at: http://dx.doi.org/10.3934/dcds.2015.35.1009 | eng_Latn | 17,954 |
Automated Enforcement of Privacy Rules and Regulations in the Cloud: Survey and Bibliography | In this paper we survey existing work on automatically processing legal, regulatory and other policy texts for the extraction and representation of privacy knowledge and rules. Our objective is to link and apply some of these techniques to policy enforcement and compliance, to provide a core means of achieving and maintaining customer privacy in an enterprise context, particularly where data is stored and processed in cloud data centres. We sketch our thoughts on how this might be done given the many different, but so far strictly distinct from one another, approaches to natural-language analysis of legal and other prescriptive texts, approaches to knowledge extraction, semantic representation, and automated enforcement of privacy rules. | On 10 March 2014, the Broadcasting Authority of Ireland (BAI) ::: published BAI Guidelines in Respect of Coverage of Local and ::: European Elections. The Guidelines set out the rules and approach ::: that should be adopted by all Irish broadcasters when covering the ::: forthcoming local and European elections. Polling for both ::: elections is scheduled to take place on 23 May 2014. | eng_Latn | 17,955 |
A Data Perturbation Method to Preserve Privacy Using Fuzzy Rules | Data mining methods analyze the patterns found in data, irrespective of the confidential information of an individual. It has led to raise privacy concerns about confidential data. Different methods are inhibited in data mining to protect these data. Privacy preserving data mining plays a major role in protecting confidential data. The paper focuses on data perturbation method to preserve confidential data present in the real-world datasets. These identified confidential data are perturbed using fuzzy membership function (FMF) and obtains fuzzy data. The mining utility such as classification and clustering methods are used. The accuracy is determined and compared between an original data and fuzzy data. The results shown in the paper proves the proposed method is efficient in preserving confidential data. | I discuss a recently unveiled feature in the dynamics of two dimensional coarsening systems on the lattice with Ising symmetry: they first approach a critical percolating state via the growth of a new length scale, and only later enter the usual dynamic scaling regime. The time needed to reach the critical percolating state diverges with the system size. These observations are common to Glauber, Kawasaki, and voter dynamics in pure and weakly disordered systems. An extended version of this account appeared in 2016 C. R. Phys. . I refer to the relevant publications for details. | kor_Hang | 17,956 |
Passive millimeter-wave imaging for security and safety applications | 77 GHz passive millimeter wave (PMMW) imaging camera for the purpose of security is developed. In order to detect ::: concealed objects in clothes without hindrance to flow of people at airport security checks, video rate imaging is realized ::: using one-dimensional imaging sensor array of 25 elements and a flapping reflector. As receiving antennas, novel ::: antipodal Fermi antenna (APFA) having required characteristics for passive imaging such as broad bandwidth to obtain ::: enough power, axially symmetric directivity with 10dB beam width of 35 degrees to obtain optimum coupling with ::: dielectric lens, narrow width geometry for high spatial resolution of imaging is used. Real-time calibration (RTC) ::: technique is introduced to eliminate the drift of receiving circuits. Interpolation technique to improve the quality of ::: image and marking software for screening of suspicious objects are also developed. High spatial resolution of 20 mm is ::: obtained by using developed imaging camera. | In hospitals, offices and other settings, professionals face the challenge of accessing and sharing sensitive content in public areas. As tablets become increasingly adopted in work environments, it is important to explore ways to support privacy that are appropriate for tablet use in dynamic, mobile workflows. In this research we consider how spatial information can be utilized to support both individual and collaborative work in a natural way while respecting data privacy. We present a proof-of-concept implementation of a proximity-aware tablet, and a range of privacy notification and control mechanisms designed for such a tablet. Results from a user study support the idea that interpersonal distance and orientation can be used to mediate privacy management for tablet interfaces. Selecting a specific design for privacy threat notification and response is highly context-dependent-for example, in health care the first priority is to not impede the fluid exchange of information. | eng_Latn | 17,957 |
Discussion on the Market-driving-type Marketing and the Market-driven-type Marketing——The Transformation of Enterprise's Marketing Conception | The marketing conception,which is the guiding thought and conduct standard relied on by the enterprise in the operational activities,is the product of the development of certain social economy.This paper probes into the differences between the market-driving-type marketing and the market-driven-type marketing,analyzes on the innovative contents of the market-driven-type marketing,and points out the necessity of developing the market-driven-type marketing. | This paper addresses mainly the problem of private data protection in network communication against eavesdropping attacks. As this kind of attacks is stealthy and untraceable, it is barely detectable for those feature detection or static configuration based passive defense approaches. We propose a Moving Target Defense(MTD) method by utilizing the protocol customization ability of Protocol-Oblivious Forwarding (POF). The novel full protocol stack randomization MTD can greatly increase the difficulty of implementing network eavesdropping attack and protect the privacy of the network communication process. | eng_Latn | 17,958 |
Privacy Informatics: A Primer on Defensive Tactics for a Society under Siege | What the world needs now is a new field of study: privacy informatics. This emerging field will fill the information-awareness gap between a trusting citizenry and the emerging digital dystopia. | A methodology to estimate security of supply in electricity generation: results for Germany until 2030 given a high level of intermittent electricity feed-in / Moritz Paulus, Katharina Grave and Dietmar Lindenberger. Institute of Energy Economics at the University of Cologne, 2011, 26 p. (EWI Working Paper, No 10/2011) http://www.ewi.uni-koeln.de/fileadmin/user_upload/Publikationen/Working_Paper/EWI_WP_11-10_Methodology_to_estimate_security_of_supply-1.pdf In this paper, we develop a methodol... | eng_Latn | 17,959 |
Privacy Support and Evaluation on an Ontological Basis | This work is concerned with user perceived privacy and how clients (which we call data subjects here) can be empowered to control their own data consistently with their own interests. To support building and evaluation of privacy-aware applications, we describe a privacy ontology, how the privacy principles relate to that and how they are influenced by the core concepts as well as by each other. We use this influence of the privacy principles to evaluate the level of privacy for a particular transaction, when applying and extending the core concepts for an application domain. | Contents: Preface Introduction Developing research questions Developing the framework for an ethical assessment Possible legitimation of whistleblowing policies Screening whistleblowing policies Towards what legitimation of whistleblowing? References Index. | eng_Latn | 17,960 |
Practical Solutions for Protecting Individual Genomic Privacy | The increasing availability of genomic data has major implications for personal privacy. The issues raised by genomic privacy reside at the crossroads of medicine, computer science, legislation and public policy. We here describe the design and development of new privacy enhancing technologies that aim to find the optimal balance between usability and privacy of genomic data in clinical care and in biomedical research. | We describe a novel method for transcript profiling based on high-throughput parallel sequencing of signature tags using a non-gel-based microtiter plate format. The method relies on the identific ... | eng_Latn | 17,961 |
American gun owners pose with weapons and explain why they bear arms .
'Guns make us safe' Jennifer, Washington .
The world is a dangerous place' Danielle, Pennsylvania .
All photos are from Kyle Cassidy's 2007 book 'Armed America: Portraits of Gun Owners in Their Homes'. The text of captions is based on paraphrasing of the interviews in that book. | By . Daily Mail Reporter . PUBLISHED: . 21:08 EST, 21 December 2012 . | . UPDATED: . 21:49 EST, 6 January 2013 . Following the shocking murder of 20 children and seven adults at Sandy . Hook last week, the debate surrounding gun control laws in the U.S has been reignited. This week President Obama has promised to bring in reforms while the powerful gun lobbyists the National Rifle Association says the answer is for armed security officers in schools. In this series of eye-opening pictures, gun-owning Americans pose with their deadly arsenal of weaponry and explain why they feel the need to bear arms. Protection: Aaron and Brittny, pictured, from Pennsylvania got their guns for protection . It's my right: 'As an American I believe it . is my natural right to own a firearm,' said Michael from Florida, right . No genocide: Ry, from Washington state said: 'I own a gun because a disarmed populace . is required for genocide and should it come around again I’m not going . to be that guy. Home protection: Avery, Miles, Gregg and Theresa, pictured, from Arizona have four rifles to protect themselves against a burglar . The Sandy Hook massacre was the second-deadliest US shooting of all-time after the Virginia Tech college attack in 2007. Adam Lanza, 20, shot his mother before driving to the school and carrying out the atrocity. The right to bear arms is enshrined in the Second Amendment of the American constitution and gun control laws have been fiercely opposed. Daughter of a cop: Danielle, from Pennsylvania says her father was a Philadelphia police . officer for more than 30 years. 'Growing up the . daughter of a cop, you learn early on that the world can be a dangerous . place.' Safe: Jennifer, Chris and Daniel, from Washington. 'Guns keep us . safe, or make us feel safe,' Jennifer says . Sick: James, from Pennsylvania, was diagnosed with cancer and found himself in need of protection. Holocaust: Kevin, from Kentucky says: ‘As a Jewish American I am cognisant of the . fact that six million of my people were turned into air pollution in the . Thirties and Forties.' | (CNN) -- Skim through the photos on Flickr or Photobucket, and you'll find pictures of cats pawing at living-room sofas, children playing in backyards and mothers gardening at home. Dig a little deeper, and you can unearth the exact locations of many of those homes, embedded in data within the pictures. Images often contain a bundle of information and various traces left by digital cameras or photo manipulation software. This data, called Exchangeable Image File Format (EXIF), is a key tool for many professionals. It can detail whether the photographer used a flash, which digital effects were applied to a picture and when the photo was taken. EXIF can also contain the precise GPS coordinates for where a photo was taken. This information is readily accessible and can be plugged into software such as Google Maps -- leading some security and photography experts to express concerns about amateurs unknowingly disclosing private information, such as the location of their home. "What could go wrong with that?" Roger Thompson, the chief research officer for digital security firm AVG, said sarcastically. Thomas Hawk, an active Flickr user and the former chief executive of competing photo site Zooomr, said EXIF is an important part of his archival process. But he has also used that data to track down someone who was harassing him online and managed to coerce an apology, he said. "I don't geotag any pictures to my house," Hawk said on the phone last week. "I think it's a huge concern. I think a lot of people don't realize or recognize what's in all of the EXIF data that they're publishing." Most gadgets ignore the geotagging component of EXIF because relatively few cameras contain the GPS chips needed to tag them. However, many smartphones, such as those from Apple and Google's Android system, let users employ this feature. Apple's and Google's systems ask each user once or a few times for permission to access their location in order to provide additional services. If they click "OK" on that popup, every photo they take is tagged with GPS coordinates. Smartphones are fast becoming the camera of choice for many people. Cameras on newer phones have come to rival dedicated point-and-shoots, and many smartphone owners carry them just about everywhere. Smartphone sales have increased 50 percent since last year, according to a report by research firm Gartner. Millions of images are uploaded to Facebook using the company's iPhone, Android and BlackBerry applications. The iPhone 3G is the most popular shooter among photographers on Yahoo's Flickr website, according to a report on that site. Judging by the abundance of pictures in Flickr's database that include geolocation data in the EXIF, some smartphone owners aren't thinking twice about opting into their devices' GPS feature. Doing so can facilitate useful tools. For example, software like iPhoto and Picasa can group images by location and display them on a map. But amateur photographers may not realize that this info stays with the image when it's uploaded to Flickr, Photobucket, Picasa Web Albums and some other photo-sharing services. (Facebook says it strips the EXIF data from all photos to protect its users' privacy.) Pictures uploaded to Photobucket by one woman show her children preparing lunch and bathing in a kitchen sink. The location data, which is displayed directly on each photo's webpage, can be inputted into Google Maps to find a satellite image of her rural home in Edmond, Oklahoma. The woman couldn't be reached for comment. "We added EXIF data a few years ago at the request of our users," Rob Newton, a spokesman for Photobucket, wrote in an e-mail. "To date, we have not received any complaints from users who were previously unaware of the GPS tagging feature." Displaying the GPS coordinates on the page can be disabled in a user's settings panel, Newton noted. However, anyone could still download the original file using a link on Photobucket and view the location info in Adobe's Photoshop or in software included with every new Mac and Windows 7 computer. Flickr's and Picasa's pages don't show the coordinates by default. But the services similarly offer links to access the original files, which can contain EXIF. "Having the ability to download the original version of photos on Flickr is an important feature for our members," a Flickr spokeswoman wrote. "However, we help people maintain their privacy by stripping the EXIF data of an image from view on the site and making the default control option to keep this information private." Users who don't want their photos tagged with GPS data can either disable the option on their cameras or run the images through software, such as Photoshop, that can remove the EXIF. "We realize not everyone wants to share this information with others," a Google spokeswoman wrote in an e-mail. She notes how to disable GPS tagging, but added: "This is a popular Picasa feature that many people find useful." Some photo services, including Facebook, TwitPic and Yfrog, strip EXIF once a file is uploaded and don't offer a way for users to access the original. For Yfrog, the lack of EXIF is a byproduct of automatic image optimizations done by the system, not something designed specifically with privacy in mind, Mike Harkey, a spokesman for the ImageShack-owned Yfrog site, wrote in an e-mail. While Facebook's system compresses some photos, it doesn't do so for every one. "For those that we don't compress, we still strip out EXIF data," Facebook spokeswoman Jaime Schopflin wrote in an e-mail. "We do this since users can unintentionally leak sensitive information in EXIF data." Thompson, the security expert from AVG, commended these efforts. "Chalk one up to Facebook for that one," he said. "One of the alarming things is that every [Facebook] application wants to access your profile and your contacts and your photos. So if they weren't stripping that [EXIF data], it would be particularly alarming." | eng_Latn | 17,962 |
Is privacy a fundamental right? | Is privacy a human right? | Is it possible to hack into Aadhar card database and get full information about a specific person? | eng_Latn | 17,963 |
'Ludicrous': privacy decision on blogger's details released | Privacy groups have blasted a decision by the Information Commissioner that found the Department of Human Services acted within the Australian Privacy Principles when it released details about a Centrelink client to a journalist last year.
The statement released by the commissioner on Monday said that the release of the information was authorised by a provision of the Australian Privacy Principles that said if a government entity held "personal information for a primary purpose, it may use or disclose it for a secondary purpose if the individual would reasonably expect it to do so, and the secondary purpose is related to the primary purpose".
Former information commissioner Timothy Pilgrim opened the investigation into the release of the information. Photo: Jeremy Piper
The commissioner launched an inquiry in March last year after an opinion piece was published in The Canberra Times by journalist Paul Malone that included personal details of blogger Andie Fox, who had previously had an opinion piece published also in The Canberra Times where she described her negative experiences dealing with Centrelink.
The details about Ms Fox were prepared by Department of Human Services staff and provided to the journalist by staff in the office of then Human Services minister Alan Tudge.
The inquiry was started by former information commissioner and privacy commissioner Timothy Pilgrim, who has since retired, and this week's decision was released by acting Information Commissioner and acting Privacy Commissioner Angelene Falk. | Hospitals may soon have to post their standard prices for patients online, under a proposed rule unveiled Tuesday by the Trump administration.
Also, the administration is seeking comments on how to stop so-called surprise billing — when patients are charged after unknowingly being seen by out-of-network providers — and how to give patients better information about the out-of-pocket costs they will face.
And officials are ramping up pressure on hospitals to give patients better access to their medical records electronically or face a penalty.
The proposed rule is the Centers for Medicare & Medicaid Services’ latest effort to give patients more information about the cost of health care and about their own medical history. The guidance applies mainly to Medicare patients and providers, but officials expect it will influence practices across the nation’s health care system. It would take effect in 2019.
Related: Trump wants to make it easier for you to access your medical records
The initiative builds on the Obama administration’s efforts to increase transparency. Hospitals are already required to provide either a list of their standard charges or their policies for allowing the public to view the prices. Trump officials want hospitals to post this information on the Internet and make it available in a way that third-party app developers can access.
The administration is also pressing providers to increase the sharing of information among hospitals so patients could see all their records, regardless of where they go for care. Currently, a hospital often gives patients access to their data through its own online portal.
“Our administration is serious about ensuring that when a patient leaves a hospital, they are able to get their medical information electronically,” said Seema Verma, the agency’s administrator. | eng_Latn | 17,964 |
Do I really need to care about my privacy online? | Do I really need to care about my privacy online if I have nothing to hide? | What is net neutrality and why is it important? | eng_Latn | 17,965 |
Driver Monitoring Devices? | Yolanda Perdomo of member station WCPN reports from Cleveland that Progressive, an Ohio based insurance company, wants policyholders to install a monitoring device in their cars, which will track whether they're speeding, tailgating or using their turn-signals. The "autograph" would allow the company to give cheaper insurance rates to safe drivers. Privacy advocates are expressing concern. | Hewlett-Packard's admission that it spied on its own board of directors and journalists has cast a spotlight on the underground market for personal information. But HP is not alone: There is a thriving network of creative con artists who gather phone records and other private data. Some of their clients are major banks and insurance companies. | eng_Latn | 17,966 |
Why do people care so little about their online privacy? | Why most people don't care about their security and privacy in the cyber space? | Why do some people still believe that global warming is not happening despite all the evidence that it is? | eng_Latn | 17,967 |
Hidden in Apple phones is a function which logs every journey you take .
Frequent Locations feature was quietly introduced to iPhones a year ago .
iPhones are able to analyse the data and work out where you live .
Apple claims the data never leaves your phone without your permission .
Professor Noel Sharkey said Apple’s ability to track people is 'terrifying' | The Frequent Locations feature was quietly introduced to iPhones a year ago . It is tracking your every move – recording the exact time you left for work, where you bought your coffee and where you like to shop. But this isn’t a futuristic spy drone or some sinister Big Brother state – it’s the iPhone sitting in your pocket. Hidden in Apple phones is a function which logs every journey. The iPhones are then able to analyse the data to figure out where you live and work, basing decisions on the frequency and timing of trips. The function – called the Frequent Locations feature – was quietly introduced to iPhones a year ago. But since access to the programme is buried beneath five layers of settings menus, few people know it exists. Apple claims the data never leaves your phone without your permission, and that it was only designed to improve mapping services. But Professor Noel Sharkey, one of Britain’s leading computing experts, described Apple’s ability to track people as ‘terrifying’. ‘This is shocking,’ he said. ‘Every place you go, where you shop, where you have a drink – it is all recorded. This is a divorce lawyer’s dream. But what horrifies me is that it is so secret. Why did we not know about this?’ Smartphones have had the ability to track their owners’ movements since they were first installed with GPS chips and mapping functions. But this feature, which is automatically installed on any iPhone with the iOS 7 or an iOS 8 operating system, is the first to display the movements clearly on a map. The phone records the date of every one of your journeys, your time of arrival and departure and how many times you have been to each address. Apple insists the data only leaves the phone if users gives their consent by selecting the Improve Maps option in the phone’s privacy menu. But campaigners say the data could be seen by a snooping boss, a jealous wife, or even seized by police or an authoritarian government. The revelation comes at the end of a week in which Apple saw £12billion wiped off its value after a glitch left iPhone 6 owners unable to get a signal – and some owners of the new slimline iPhone 6 Plus bent their frames. In an open letter this month, Apple chief executive Tim Cook said: ‘Our business model is very straightforward. We don’t “monetize” the information on your iPhone or in iCloud.’ But Professor Sharkey said: ‘Apple might promise not to use our location information for advertising. And many of our authorities might be quite benevolent at the moment. But if you put that information in someone else’s hands, then it becomes powerful, and in some cases, dangerous.’ To disable Frequent Locations, select Clear History and make sure Improve Maps is deselected . The Frequent Locations function is automatically installed on any phone with iOS 7 or iOS 8. To access Frequent Locations, go into Settings, choose the Privacy option and then Location Services. Go right down to the bottom and select System Services – then click Frequent Locations. Your data will be displayed under a History heading divided up into cities and districts – click on each one to see how your phone monitors, analyses and maps everywhere you go. To disable Frequent Locations, select Clear History and make sure Improve Maps is deselected. Finally, turn off the Frequent Locations tab. This does not stop data being recorded, it only stops it being packaged up in a map. To stop it being logged at all, you can disable Location Services in the Privacy menu – but this will leave you unable to use your phone’s mapping software. | By . Associated Press . PUBLISHED: . 16:17 EST, 11 October 2013 . | . UPDATED: . 03:09 EST, 14 October 2013 . Google wants your permission to use your name, photo and product reviews in ads that it sells to businesses. The internet search giant is changing its terms of service starting Nov. 11, but it will only affect users with Google+. Your reviews of restaurants, shops and products, as well as songs and other content bought on the Google Play store could show up in ads that are displayed to your friends and connections when they search on Google. Google changes: The search giant has outlined the updates on its policies and principles page . However, you can opt out of sharing. Google's move follows a similar proposal by Facebook. The social network in August said it would show users' faces and names in ads about products they clicked to 'like'. That proposal was criticized by privacy groups. They asked the Federal Trade Commission to look into the matter. Google outlined the new changes on its website: 'Your Profile name and photo might appear in Google products (including reviews, advertising and other commercial contexts). 'You can control whether you image and name appear in ads via the Shared Endorsements setting' Google went on to explain why they're making the changes, writing: 'We want to give you and your friends and connections the most useful information. 'Recommendations from people you know can really help. So your friends, family and others may see your Profile name and photo and content like the reviews you share or the ads you +1'd.' More information about the changes can be found on Google's policies and principles page. Google's New York City headquarters on 8th Avenue pictured . | eng_Latn | 17,968 |
New Service Aims To Make Texting Secure | Text messaging isn't very secure — copies of messages pass through multiple mobile carriers' servers. A new service called TigerText hopes to change that paradigm by offering a secure texting system where messages are encrypted. The service has piqued the interest of hospitals. | Google's popular art selfie feature isn't available in Illinois or Texas. NPR's Mary Louise Kelly talks with Matthew Kluger, a law professor at NorthwesternUniversity, about how biometric privacy laws are affecting tech companies in certain states. | kor_Hang | 17,969 |
Desktop manager examples: Gnome, Unity. Display manager examples: GDM, LightDM. What is the split in responsibilities of these two types of managers? What functions do they each provide? And are they both dependent on X server, in what way? Thanks | I'm having a really hard time trying to understand what the differences between a desktop environment and a window manager are? EDIT: From this : There are basically three layers that can be included in the Linux desktop: X Windows – This is the foundation that allows for graphic elements to be drawn on the display. builds the primitive framework that allows moving of windows, interactions with keyboard and mouse, and draws windows. This is required for any graphical desktop. Window Manager – The Window Manager is the piece of the puzzle that controls the placement and appearance of windows. Window Managers include: , , , , , etc. Requires X Windows but not a desktop environment. Desktop Environment – This is where it begins to get a little fuzzy for some. A Desktop Environment includes a Window Manager but builds upon it. The Desktop Environment typically is a far more fully integrated system than a Window Manager. Requires both X Windows and a Window Manager. Examples of desktop environments are , , , among others) | I've observed several incidents where users inadvertently posted detailed, sensitive information. For example, a Server Fault user who posted a question with working login credentials to his actual production server, or the Stack Overflow user who posted actual medical records as example data for his question. What should be the procedure for handling such cases? | eng_Latn | 17,970 |
I try to hide my site information from Alexa or not show some country-specific information. How can I do this? Will this be done by blocking the Alexa robot or do I have to do something else? | My competitor is using Alexa to see what I am doing. I need to get stop Alexa from including my sites in their rankings. How can I do so? Is it possible to deny access to any visitor with the Alexa toolbar and deny access to Alexa bot requests? | Is it correct to say "What was your name?"? The reason I am asking this is, generally the name of the person will not change. One should say "What is your name?" | eng_Latn | 17,971 |
Claim Public Disclosure of Private Facts | When someone publicly discloses sensitive information about your private life, you may have a legal claim you can sue on. This tort is called the “public disclosure of private facts.” | This wikiHow teaches you how to hide your phone number from public viewing on Facebook. This process is different than removing a phone number entirely . | eng_Latn | 17,972 |
What can I do if I post confidential information? | What should I do if a user posts sensitive information as part of a question or answer? | Why would perfectly similar data have 0 mutual information? | eng_Latn | 17,973 |
How do I protect myself if a scammer has my name, email, state and birthdate? | I gave a scammer my telephone number, address, and name. How bad is it? | Moderncv adding date of birth to personal information | eng_Latn | 17,974 |
Sue for Invasion of Privacy | You have the right to be left alone. [1] When someone invades that privacy, you may be able to sue in court and get compensated for your injury. An invasion of privacy can take many different forms, and whether you have a valid lawsuit will depend on the state you live in as well as the facts of your case. | This wikiHow teaches you how to set privacy preferences for each app that keeps track of your iPhone's location using Location Services. | eng_Latn | 17,975 |
How to convince and/or ask researchers to share data? | Requesting raw data from previously published research | Why would perfectly similar data have 0 mutual information? | eng_Latn | 17,976 |
risks of online security? | The risks and dangers of not having sufficient privacy or security on your SITE:\n\n(1) Your data can be taken AND/OR revised.\n\nIt summarize only to either of the above point (i.e. HACK). Remember the recent happened to the prophet cartooning? More Denmark’s websites were defaced. | dont do it there are weirdos out there who take pics of u being on cam using cameras etc no reason too | eng_Latn | 17,977 |
Why doesn't it matter what people think of you? | Why does it matter to you what people think about you? | Do I really need to care about my privacy online if I have nothing to hide? | eng_Latn | 17,978 |
Is Aadhar card taking people's privacy? | How does the collection of biometric details for the Aadhar card become an invasion of privacy? | Do you think ban on NDTV is to spoil its credibility and project it as an anti national channel? | eng_Latn | 17,979 |
What is a secret which you would not tell anybody in real life? | What is a secret which you would not tell anybody in real life, but would on Quora using anonymity? | What is so secretive about secret service? | eng_Latn | 17,980 |
Is anonymous 100% anonymous? | Will I be 100% anonymous by asking a question anonymously? | Is it possible to hack NASA's New Horizons satellite? | eng_Latn | 17,981 |
What vulnerability scan show personally? | What vulnerability scan showed personally? | What would the consequences be if someone hacked the anonymity feature on Quora and everyone who thought they were anonymous would be exposed? | eng_Latn | 17,982 |
Is anything truly anonymous? | Is anonymous really anonymous? | What are some of the unsaid rules in Quora? | eng_Latn | 17,983 |
Why don't some people care about online privacy? | Why do people care so little about their online privacy? | Why is a large part of people in Quora so pretentious and arrogant? | eng_Latn | 17,984 |
Is anonymous 100% anonymous? | Is anonymous really anonymous? | Is it possible to hack NASA's New Horizons satellite? | eng_Latn | 17,985 |
What would be the impact of Quora getting hacked and all anonymous identities exposed? | What would the consequences be if someone hacked the anonymity feature on Quora and everyone who thought they were anonymous would be exposed? | What would happen if Donald Trump was assassinated? | eng_Latn | 17,986 |
The only options on the location privacy prompt are 'Allow' or 'Don't Allow', with a 'Remember my decision for one day' modifier checkbox as well. But what if there's a site that I trust in perpetuity? I want to give it permission to access my location forever. Why can't I do that? Safari 8.0 on Mac OS X 10.10 Yosemite | In iOS, I only need to be asked once whether I want to allow a website to share my location data. Is it possible to permanently do this in OS X version of Safari as well? | In iOS, I only need to be asked once whether I want to allow a website to share my location data. Is it possible to permanently do this in OS X version of Safari as well? | eng_Latn | 17,987 |
I have searched other results and read many of them but I could not get an enough information. My question is that can a website see my MAC address or can they have an information about that I'm the same person under these conditions: I am using a VPN and I use two IPs: first one is normal one, the second one is the VPN's IP. I use two browsers to hide behind browser fingerprinting. I use both browsers with Incognito Mode. I always use one for normal IP, one for the VPN IP. I do not know that if the website uses cookies or not. But can they collect an enough information to prove that these two identities belong to same person? Is there any other way for them to see that I am the same person? I use different IPs, different browsers and I use both browsers in incognito mode. I even changed one of browsers language to only English. So even if they collect my info from browser, they will see two browsers using different languages. (Addition after edit): So I have changed my IP and browser information and the website can not reach this information anymore to prove that I am the same person using two accounts. Then let's come to the title: Can they see my MAC address? Because I think that it is the last way that they can identify me and my main question is that. I wrote the information above to mention that I changed IPs and I have some precautions to avoid browser fingerprinting (btw my VPN provider already has a service about blocking it). I wrote them because I read similar advices in some related questions but my question is that can they see my MAC address (or anything else that can make me detected) despite all these precautions. And lastly, Is there an extra way to be anonymized that I can do? For example, can my system clock or anything else give an information? Thanks in advance. | When you hit up a site, such as cnn.com, does the TCP/IP packet contain the MAC address of your network card? Could cnn.com theoretically record my MAC address? | , and 1 still show the old bar. 1 See | eng_Latn | 17,988 |
I do not understand what should be here: He wants to be able to see all users whose data he has an/the... access to. | What article should be used in the following sentence? He was English by [a/the/] blood. I feel there should be a zero article here, but I was taught that the zero article is impossible in English. | Is there a way to view the site without having to look at reputation information? I do not want to track my rep information or see anyone else's. I think that'll let me focus more on the questions themselves. Is anyone else interested in this feature? I don't see anything on Stack Overflow itself, but are there any add-ins or scripts that do this? | eng_Latn | 17,989 |
Is it a good practice to store primary key values in form elements for storing data after form submission? For example if I have a select tag inside my form like this: <select name="city"> <option value="3">Kolkata</option> <option value="7">Bangalore</option> <option value="1">Delhi</option> <option value="4">Mumbai</option> </select> In my City table they are stored like this: Id Name -- ---- 1 Delhi 3 Kolkata 4 Mumbai 7 Bangalore After form submission, extraction of values is pretty simple and we directly get the foreign key value without looking up the City table. However, I feel that this could be a major problem since one can easily manipulate the values through developer tools. If not this approach, what is the general and widely accepted norm? EDIT Since this question has been suggested as a duplicate of , I've added my reason against it: This question deals with the aspect of general practice followed by developers unlike the other with deals with security concerns if a particular practice is followed. | I've heard that exposing database IDs (in URLs, for example) is a security risk, but I'm having trouble understanding why. Any opinions or links on why it's a risk, or why it isn't? EDIT: of course the access is scoped, e.g. if you can't see resource foo?id=123 you'll get an error page. Otherwise the URL itself should be secret. EDIT: if the URL is secret, it will probably contain a generated token that has a limited lifetime, e.g. valid for 1 hour and can only be used once. EDIT (months later): my current preferred practice for this is to use UUIDS for IDs and expose them. If I'm using sequential numbers (usually for performance on some DBs) as IDs I like generating a UUID token for each entry as an alternate key, and expose that. | The new Top-Bar does not show reputation changes from Area 51. | eng_Latn | 17,990 |
Limit public profile information Is it possible to restrict profile information about a specific Stack Exchange site ? For example, I'm using StackExchange for SO, Software QA, Personal Productivity, Area 51, but I would like to only show my accounts on SO and QA, hiding others profiles. A kind of separation between professional and "personal" stuff. Thanks | Allow users to hide connections between accounts This feature request is inspired by the question on Programmers.SE on . Stack Overflow is a site aimed at professional programmers, and it is used by some employers and some employees to examine or showcase the candidates abilities. I don't see any problem with that, but there is one aspect I'm a bit concerned about. Certain SE sites are far more private than the professional sites like SO. Anyone that participates in Christianity, Judaism, Islam or Biblical Hermeneutics is likely giving out a significant amount of information about their personal belief or world view to anyone who can connect the user name to the actual person. Another example would be controversial topics on Skeptics or Politics; not everyone would like to give their employer access to that kind of information. The fundamental problem is that the SE platform does not allow for any separation inside one account. Of course one could create separate accounts for private and professional topics, but that requires a significant amount of clairvoyance and a rather annoying user experience juggling separate browsers to log into different accounts at once. An additional problem is that SE has automatic user merge features that can be triggered by logging into two accounts in the same session. I'm not sure how they work exactly, but I suspect that having your two accounts accidentally merged is a real danger if you are not careful. There should be a mechanism to hide the connection between SE accounts, without having to use separate OpenIDs. For example, if I would like to use my SO account in job applications, I should be able to separate it from all my other accounts. The separation would only be for the publicly accessible part, moderators could still be allowed to see the connection between accounts. And behind the scenes it would just work as it is now, just without any links between the accounts. The aspects that would need to be changed that I can think of are the accounts tab in the user profile, that shouldn't show any connections for separated profiles copying the user profile to other sites should not work for separated profiles the network profile should not show the connections between separated profiles Area 51 should also not show the profile connections This separation would not have to be bulletproof, but it should prevent users googling a specific person to make connections the user does not want to make public. | Is there flair for Careers.SO? Are there any image badges like those on for Careers.SO? I would like to add a nice image to my website profile. | eng_Latn | 17,991 |
Make Hidden Files on Ubuntu | Sometimes, you may want to protect some files from being seen by standard means and to keep them from being messed with by people who don't know what they are doing. | Have you ever thought 'Hmm, my external CD drive would look MUCH better if no one knew what it was.'? Here is how to do it. | zsm_Latn | 17,992 |
Ubuntu uses the information about searches to show the user ads to buy various things from Amazon. Amazon commits many wrongs (see ); by promoting Amazon, Canonical contributes to them. However, the ads are not the core of the problem. The main issue is the spying. Canonical says it does not tell Amazon who searched for what. However, it is just as bad for Canonical to collect your personal information as it would have been for Amazon to collect it. Same question has been asked here But I don't have the tab 'search results' on my 12.04 distro. How can I disable this? I understand that canonical uses this business plan in order to make a living and I really would help in their research as long as the data is preserved anonymously, but I really want to have control over this option, so when I search for something to buy, then enable it so I can help canonical gather this data, otherwise I would like this option disabled. Thank you | How can I disable Amazon search results in the Dash? | In fact, of these, only Charcoal shows a recent time stamp. | eng_Latn | 17,993 |
Deny full node access for anonymous users | Node access based on view mode | Can we re-request features that were declined a sufficient while ago? | eng_Latn | 17,994 |
Should we remove personal information (name/email) from answers? | What should I do if a user posts sensitive information as part of a question or answer? | Moderncv adding date of birth to personal information | eng_Latn | 17,995 |
Is it okay to use Data Explorer as a recruiting tool? | A Terms of Service update restricting companies that scrape your profile information without your permission | Entries I can safely exclude doing backups | eng_Latn | 17,996 |
Hiding a Field User-Based - 50 Users Assigned to same Profile, hide ONE Filed only to ONE User Hide a Field from ONE PARTICULAR USER out of 50 Users having the same Profile I have 50 Users assigned to a Profile called Sales. I have a Custom Object called "Commission". I have a Field called "Comission Amount" this field contains confidential data and the Management would like to HIDE this ONE Field from ONE User who is one amongst the Users with Sales Profile. What we want to achieve is that out of 50 Users with Sales Profile, we should HIDE this ONE Field from this Object to this ONE particular user who has Sales Profile. How to achieve this? The User can have access to Read / Write View the Object and have access to all the other Fields on this Object except for this One Field called Comission Amount.. What's the best Solution? Note: We do not want to create a Custom Profile for this Particular User. | Hide a Field From ONE User Scenario: If I had a Custom Profile / Standard Profile, say Sales,and I have 50 Users assigned to the same Profile and had same Permission / Access on a particular object (Could be Standard or Custom Object), if I were to Hide a Field ONLY TO ONE USER, which would be a better Solution to achieve this WITHOUT EDITING OR TOUCHING THE PROFILE?? Option 1: Create a Custom Profile for this particular User and give CRED access (I know this one isn't a good solution as I got a Thumbs-down from a Technical Architect) Option 2: Create a Permission Set - Go to the particular Object,say, Accounts, Object Permission Enabled -->Field Permissions-->Remove READ Access - This would make this particular field hidden from the Object to the Profile. Then Assign this Permission to particular User whom I don't want to see this field. I would go with the 2nd option but I still hear a groan. Where am I going wrong? How would you hide a particular field from ONE User out of 10 Profiles who have the same Access Rights? What's the best possible solution to hide a Filed from only one User out of 10 Users who have the same Profile. | Where does Drupal store its content? I have been currently learning Drupal while trying to duplicate a Drupal application into CakePHP. I have been looking at the database tables to know where data is being stored so I can safely migrate any data or study how it is working. I have researched and have come across questions like: So far, I have only seen the title in my Drupal (7) installation. What I have seen in my node revisions table for a recipe content type, which includes fields like, field_ingredients, field_instructions, field_description, field_preptime, field_cookingtime, just the title of the recipe. This is a sample record on my node_revision table. nid | vid | title | log | timestamp | status | comment | promote | sticky ------------------------------------------------------------------------------------------- 1 | 1 | Awesome Sauce | | 1369998600 | 1 | 2 | 1 | 0 As you can see I can only see the title. Where are the other field contents? | eng_Latn | 17,997 |
Log Your Car: The Non-invasive Vehicle Forensics | The Scyther Tool: Verification, Falsification, and Analysis of Security Protocols | S3 - Guidelines on the treatment of psoriasis vulgaris (English version). Update. | eng_Latn | 17,998 |
NPR Online Privacy Policy | NPR Online Privacy Policy Highlights Note: The NPR Online Privacy Policy ("Privacy Policy") has been updated with an effective date of June 30, 2018. Please review the updated Privacy Policy carefully before using the NPR Services. By using any of the NPR Services, you consent to the terms of the updated Privacy Policy. This section highlights important features of the Privacy Policy. Please scroll down to see the full Privacy Policy or click on "Read more" to learn more about a specific area. Scope of Privacy Policy NPR owns, operates, or provides access to NPR.org and NPR's mobile applications, email newsletters, and other sites, digital platforms and interactive services provided by NPR that link to or refer to the Privacy Policy (collectively "NPR Services" or "our Services"). This Privacy Policy applies only to the NPR Services and does not govern the separate websites, applications, newsletters, platforms and services of NPR Member stations or of any third parties that may link to or be linked to from the NPR Services. NOTICE TO EU RESIDENTS: Our handling of information about EU residents is governed by the NPR Privacy Notice for EU Residents, effective May 25, 2018. This Privacy Policy does not apply to EU residents. Children If you are a parent or guardian, we encourage you to become involved in your children's online experience, and to share your knowledge and experience with your young ones. If you are under 13, please do not register for the NPR Services or provide us with any contact or other information, including your name, address or email address. If you are between the ages of 13 and 18, you must obtain permission from your parent or guardian before registering for the NPR Services or otherwise sending any contact or other information to NPR. Information You Provide Directly Through Our Services We and our service providers collect a variety of contact and other information about you that you provide directly through our Services, including your name, email address, postal address, telephone number, password, age, payment card information, country of residence, communications and content preferences, and your favorite Member stations. We may collect such information when you: Register for an NPR account, application programming interface (API) content access, or any NPR email newsletter. Email, text or otherwise share a story from any of the NPR Services. Contact us for information or to ask a question. Make a purchase from the NPR Shop. Post, upload, or otherwise submit a comment, story idea, essay, photo, or other content to NPR. Register for an NPR tour or event or any contest we sponsor. Apply for a job, internship or fellowship at NPR. If you choose to participate in a survey, we may ask you to provide your date of birth, gender, education level, information about your employment, income level and other information. Make a donation to NPR or an NPR Member station or submit a related inquiry. Otherwise volunteer information to us or respond to a request for information through any of our Services. If you do not consent to the collection, use or sharing of this type of information in the manner described in the Privacy Policy, please do not provide us with such information. By providing such information, you are "opting in" to the collection, use and sharing of this information in accordance with the Privacy Policy. Information Collected Automatically Through Technology As you navigate our Services, we and our service providers also automatically collect a variety of information about your interactions with our Services. Depending on which NPR Services you use and how you access them, the information collected automatically may include: The Internet Protocol address (IP address) of the computer or device you used to access an NPR Service and information about your Internet Service Provider. The website, application, platform or service you visited before and after visiting an NPR Service. Information about your computer or mobile device, and its browser, operating system, settings and software. Unique device identifiers on the mobile device you used to access an NPR Service, including, as applicable, the Apple IDFA (Identifier for Advertisers) or Google Android Advertising ID. Your approximate geographic location information (derived from request header information, such as your IP address) and/or more precise location if you have given NPR explicit consent to receive this information for an NPR mobile application on your mobile device. Automobile make (for certain connected car platforms). The dates, times, duration and frequency of your interactions with our Services, any search terms you enter, the media files you listen to, download, view, email, text or otherwise share, favorites you select, and your navigation path through our Services. Listening data, including information about your interactions with NPR podcasts and other media files. Information about your interactions with | Each month, we listen to hundreds of new electronic music tracks, test the standouts on loud speakers and highlight the best of the best in a 30-minute mix. And we're particularly excited about what we heard during July — it was tough to narrow this list down to six songs. You can stream this month's mix here or through NPR Music's SoundCloud account. If you'd rather just hear each song individually, check out the playlist below. You can keep up with our favorite discoveries on Twitter by following @Sami_Yenigun and @spotieotis. | kor_Hang | 17,999 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.