Understand and Measure Privacy
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Submitted by JessieLzh on Wed, 01/03/2018 - 12:16pm
Recent improvements in computing capabilities, data collection, and data science have enabled tremendous advances in scientific data analysis. However, the relevant data are often highly sensitive (e.g., Census records, tax records, medical records). This project addresses an emerging and critical scientific problem: Privacy concerns limit access to raw data that might reveal information about individuals. Techniques to "sanitize" such data (e.g., anonymization) could have negative impact on the quality of the scientific results that use the data.
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Submitted by Sameer Patil on Wed, 01/03/2018 - 12:11pm
The explosion in data gathering has greatly exacerbated existing privacy issues in computing systems and created new ones due to the increase in the scale and the scope of available data as well as the advances in the capabilities of computational data analysis. Software professionals typically have no formal training or education on sociotechnical aspects of privacy. As a result, addressing privacy issues raised by a system is frequently an afterthought and/or a matter of compliance-check during the late phases of the system development lifecycle.
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Submitted by Kemal Akkaya on Wed, 01/03/2018 - 12:09pm
The modernized Smart Grid (SG) is expected to enable several new applications such as dynamic pricing, demand response and fraud detection; however, collection of such fine-grained data raises privacy issues. This project aims to design and implement several novel mechanisms for securing data collection and communication in SG Advanced Metering Infrastructure applications while preserving user privacy when the data are to be accessed.
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Submitted by Rui Chen on Wed, 01/03/2018 - 12:06pm
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Submitted by Peng Liu on Wed, 01/03/2018 - 9:44am
To better articulate privacy as a dynamic and dialectic phenomenon in a Web 2.0 world, this project proposes a set of basic empirical research activities to investigate three aspects of privacy in online social networks: conceptualization, intervention, and awareness.
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Submitted by Norman Sadeh on Tue, 01/02/2018 - 8:44pm
Natural language privacy policies have become a de facto standard to address expectations of notice and choice on the Web. Yet, there is ample evidence that users generally do not read these policies and that those who occasionally do struggle to understand what they read. Initiatives aimed at addressing this problem through the development of machine implementable standards or other solutions that require website operators to adhere to more stringent requirements have run into obstacles, with many website operators showing reluctance to commit to anything more than what they currently do.
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Submitted by Keshab Parhi on Tue, 01/02/2018 - 4:23pm
Hardware security, whether for attack or defense, differs from software, network, and data security in that attackers may find ways to physically tamper with devices without leaving a trace, and mislead the user to believe that the hardware is authentic and trustworthy. Furthermore, the advent of new attack modes, illegal recycling, and hard-to-detect Trojans make hardware protection an increasingly challenging task. Design of secure hardware integrated circuits requires novel approaches for authentication that are ideally based on multiple layers of protection.
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Submitted by Mohd Anwar on Tue, 01/02/2018 - 3:57pm
As the use of Web applications has increased, malicious content and cyber attacks are rapidly increasing in both their frequency and their sophistication. For unwary users and their organizations, social media sites such as Tumblr, Facebook, MySpace, Twitter, and LinkedIn pose a variety of serious security risks and threats. Recent studies show that social media sites are more in use for delivering malware than were previously popular methods of email delivery. Because of this, many organizations are looking for ways to implement effective security policies.
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Submitted by Fariborz Farahmand on Tue, 01/02/2018 - 2:54pm
Considerable research in the field has been focused on developing new technologies to enhance privacy; encryption of personal data is often presented as a potential solution. Many of the technologies resulting from this research are not being effectively utilized because of issues rooted in human judgment under risk and uncertainty. The majority of existing models and products related to human judgement are based on a limited number of documented incidents and on questionable assumptions about user intent and behavior.
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Submitted by Jerry Cheng on Tue, 01/02/2018 - 2:50pm
This project aims to address privacy concerns of smartphone users. In particular, it investigates how the usages of the smartphone applications (apps) may reshape users' privacy perceptions and what is the implication of such reshaping. There has been recent work that investigates privacy leakage and potential defense mechanisms. However, so far there is only limited understanding on the consequences of such privacy losses, especially when large amount of privacy information leaked from smartphone users across many apps.
