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Hardware Performance Counter-Based Malware Identification and Detection with Adaptive Compressive Sensing

Xueyang Wang, Sek Chai , Michael Isnardi , Sehoon Lim , and Ramesh Karri Hardware Performance Counter-based (HPC) runtime checking is an effective way to identify malicious behaviors of malware and detect malicious modifications to a legitimate program’s control flow. To reduce the overhead in the monitored system which has limited storage and computing resources,...

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Finding Sensitive Accounts on Twitter: An Automated Approach Based on Follower Anonymity

Sai Teja Peddinti, Keith W. Ross, and Justin Cappos We explore the feasibility of automatically finding accounts that publish sensitive content on Twitter, by examining the percentage of anonymous and identifiable followers the accounts have. We first designed a machine learning classifier to automatically determine if a Twitter account is anonymous or identifiable. We then...

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Security verification of 3rd party intellectual property cores for information leakage

Jeyavijayan Rajendran, A Dhandayuthapany, Ramesh Karri, V Vedula Globalization of the system-on-chip (SoC) design flow has created opportunities for rogue intellectual property (IP) vendors to insert malicious circuits (a.k.a. hardware Trojans) into their IPs. We propose to formally verify third party IPs (3PIPs) for unauthorized information leakage. We validate our technique using Trojan benchmarks from...

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Dynamic Privacy For Distributed Machine Learning Over Network

Tao Zhang and Quanyan Zhu Privacy-preserving distributed machine learning becomes increasingly important due to the recent rapid growth of data. This paper focuses on a class of regularized empirical risk minimization (ERM) machine learning problems, and develops two methods to provide differential privacy to distributed learning algorithms over a network.

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Characterizing user behaviors in location-based find-and-flirt services: Anonymity and demographics

Minhui Xue, Limin Yang,  Keith W. Ross, and Haifeng Qian In this paper, we explore: (i) if one gender tends to use the People Nearby service more than another; (ii) if users of People Nearby are more anonymous than ordinary WeChat users; (iii) if ordinary WeChat users are more anonymous than Twitter users. We also take an in-depth examination of the user...

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Interdependent Network Formation Games

Juntao Chen and Quanyan Zhu Designing optimal interdependent networks is important for the robustness and efficiency of national critical infrastructures. Here, we establish a two-person game-theoretic model in which two network designers choose to maximize the global connectivity independently. This framework enables decentralized network design by using iterative algorithms.

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Do You See What I See? Differential Treatment of Anonymous Users

Sheharbano Khattak, David Fifield, Sadia Afroz, Mobin Javed, Srikanth Sundaresan, Vern Paxson, Steven J. Murdoch, and Damon McCoy The utility of anonymous communication is undermined by a growing number of websites treating users of such services in a degraded fashion…We conduct the first study to methodically enumerate and characterize the treatment of anonymous users as...

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Understanding Craigslist Rental Scams

Youngsam Park, Damon McCoy, and Elaine Shi Fraudulently posted online rental listings, rental scams, have been frequently reported by users. However, our understanding of the structure of rental scams is limited. In this paper, we conduct the first systematic empirical study of online rental scams on Craigslist. This study is enabled by a suite of...

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Systems, Processes and Computer-Accessible Medium for Providing Logic Encryption Utilizing Fault Analysis

Ozgur Sinanoglu, Youngok Pino, Jeyavijayan Rajendran, and Ramesh Karri Exemplary systems, methods and computer-accessible mediums can encrypting a circuit by determining at least one location to insert at least one gate in the circuit using a fault analysis, and inserting the at least one gate in at least one section of the at least one...