Information privacy

About: Information privacy is a research topic. Over the lifetime, 25412 publications have been published within this topic receiving 579611 citations. The topic is also known as: data privacy & data protection.

Valuating privacy

Abstract: In several experimental auctions, participants put a dollar value on private information before revealing it to a group. An analysis of results show that a trait's desirability in relation to the group played a key role in the amount people demanded to publicize private information. Because people can easily obtain, aggregate, and disperse personal data electronically, privacy is a central concern in the information age. This concern is clear in relation to financial data and genetic information, both of which can lead to identity abuse and discrimination. However, other relatively harmless information can also be abused, including a person's gender, salary, age, marital status, or shopping preferences. What's unclear is whether it's the fear of such abuse that actually causes people's stated hesitance to reveal their data. Our hypothesis - and the motivation for our study - is that people reveal information when they feel that they're somewhat typical or positively atypical compared to the target group. To test this hypothesis, we conducted experiments that elicit the value people place on their private data. We found, with great significance (more than 95 percent statistical confidence) that a linear relationship exists between an individual's belief about a trait and the value he or she places on it. That is, the less desirable the trait, the greater the price a person demands for releasing the information. Furthermore, we found that small deviations in a socially positive direction are associated with a lower asking price.

Privacy-Enhanced Data Aggregation Scheme Against Internal Attackers in Smart Grid

Abstract: According to related research, energy consumption can be effectively reduced by using energy management information of smart grids. In smart grid architecture, electricity suppliers can monitor, predicate, and control energy generation/consumption in real time. Users can know the current price of electrical energy and obtain energy management information from smart meters. It helps users reduce home's energy use. However, electricity consumptions of users may divulge the privacy information of users. Therefore, privacy of users and communication security of the smart grid become crucial security issues. This paper presents a secure power-usage data aggregation scheme for smart grid. Electricity suppliers can learn about the current power usage of each neighborhood to arrange energy supply and distribution without knowing the individual electricity consumption of each user. This is the first scheme against internal attackers, and it provides secure batch verification. Additionally, the security of the proposed scheme is demonstrated by formal proofs.

The Creation and Analysis of a Website Privacy Policy Corpus

Abstract: Website privacy policies are often ignored by Internet users, because these documents tend to be long and difficult to understand. However, the significance of privacy policies greatly exceeds the attention paid to them: these documents are binding legal agreements between website operators and their users, and their opaqueness is a challenge not only to Internet users but also to policy regulators. One proposed alternative to the status quo is to automate or semi-automate the extraction of salient details from privacy policy text, using a combination of crowdsourcing, natural language processing, and machine learning. However, there has been a relative dearth of datasets appropriate for identifying data practices in privacy policies. To remedy this problem, we introduce a corpus of 115 privacy policies (267K words) with manual annotations for 23K fine-grained data practices. We describe the process of using skilled annotators and a purpose-built annotation tool to produce the data. We provide findings based on a census of the annotations and show results toward automating the annotation procedure. Finally, we describe challenges and opportunities for the research community to use this corpus to advance research in both privacy and language technologies.

Distributing the power of a government to enhance the privacy of voters

Abstract: In this paper, we distribute the functions of the government in the cryptographic election scheme of [CoFi85]. In so doing, we are able to achieve privacy of individual votes in a much stronger sense without giving up any of the previously attained properties of robustness or veriability. This gives an electronic mechanism for holding a large-scale election amongst untrusted parties which is far more useful in “realworld” applications than the previous scheme.