Foster Multidisciplinary Approach
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Submitted by Katherine Stange on Tue, 11/14/2017 - 10:59am
This project advances the understanding of number theory, geometry, and cryptography. Number theory and geometry are among the oldest and most central topics in mathematics, while their application to cryptography underlies modern cybersecurity. The project focuses on the relationships between number-theoretic information and geometric structures such as elliptic curves, circle packings, and lattices.
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Submitted by Jianping Fan on Tue, 11/14/2017 - 10:35am
The objective of this project is to investigate a comprehensive image privacy recommendation system, called iPrivacy (image Privacy), which can efficiently and automatically generate proper privacy settings for newly shared photos that also considers consensus of multiple parties appearing in the same photo. Photo sharing has become very popular with the growing ubiquity of smartphones and other mobile devices.
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Submitted by Jessica Vitak on Tue, 11/14/2017 - 9:49am
The increasing ubiquity of mobile technologies creates unique privacy and surveillance challenges for users. These problems are global, but the way users, organizations, and governments approach these challenges varies based on cultural norms around privacy. This cross-cultural project evaluates how mobile users in the U.S. and the Netherlands think about and make decisions about their privacy when using mobile apps.
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Submitted by Jeffrey Hoffstein on Tue, 11/14/2017 - 9:43am
Fully homomorphic encryption (FHE) is a promising new technology that enables an untrusted party to efficiently compute directly on ciphertexts. For instance, with FHE a cloud server without access to the user's encrypted content can still provide text search services. An efficient FHE scheme would significantly improve the security of sensitive user data stored and processed on cloud servers. Significant progress has been made in bringing FHE proposals closer to practice.
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Submitted by Jaideep Vaidya on Mon, 11/13/2017 - 4:00pm
Social networks provide many benefits, but also give rise to serious concerns regarding privacy. Indeed, since privacy protections are not intrinsically incorporated into the underlying technological framework, user data is still accessible to the social network and is open to misuse. While there have been efforts to incorporate privacy into social networks, existing solutions are not sufficiently lightweight, transparent, and functional, and therefore have achieved only limited adoption.
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Submitted by Jaideep Vaidya on Mon, 11/13/2017 - 3:34pm
Big data analytics can revolutionize innovation and productivity across diverse domains. However, this requires sharing or joint analysis of data, which is often inhibited due to privacy and security concerns. While techniques have been developed to enable the safe use of data for analysis, none of these work for the critical task of outlier detection. Outlier detection is one of the most fundamental data analysis tasks, useful in applications as far ranging as homeland security, to medical informatics, to financial fraud.
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Submitted by Huijia Lin on Mon, 11/13/2017 - 12:36pm
Outsourcing storage to the cloud has become more widespread in recent years; however, cloud storage services are constantly exposed to a number of non-trivial adversarial threats. This work addresses security risks arising from the leakage of access patterns, which is the ability of an adversary to detect when the same item is accessed repeatedly on a storage server, which has been shown to substantially impact data privacy.
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Submitted by Huijia Lin on Mon, 11/13/2017 - 12:32pm
Many organizations and individuals rely on the cloud to store their data and process their analytical queries. But such data may contain sensitive information. Not only do users want to conceal their data on a cloud, they may also want to hide analytical queries over their data, results of such queries, and data access patterns from a cloud service provider (that may be compromised either from within or by a third party).
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Submitted by Gwendolyn Lee on Mon, 11/13/2017 - 7:52am
As companies collect consumer data in increasingly larger quantity and mine the data more deeply, trade-offs arise with respect to companies' practices about information privacy. A company may choose practices that augment targeted advertisements or services. However, the financial rewards associated with privacy practices are highly uncertain, since they are affected by a company's competition with rivals.
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Submitted by Florence Hudson on Mon, 11/13/2017 - 6:13am
The 2011 Federal Cybersecurity Research and Development Plan cites "Accelerating Transition to Practice (TTP)" as one of five strategic objectives in the Cyber Security and Information Assurance (CSIA) Program Component Area. TTP remains a strategic objective of Agencies which fund cybersecurity research, including NSF. However, the NSF cybersecurity portfolio contains only a small amount of security research that has been transitioned into operational activities.
