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Abstract—While personal data privacy is threatened by online
social networks, researchers are seeking for privacy protection
tools and methods to assist online social network providers
and users. In this paper, we aim to address this problem by
investigating how to quantitatively evaluate the privacy risk, as
a function of people’s awareness of privacy risks as well as
whether their friends can be trusted to protect their personal
data. We present a trust-aware privacy evaluation framework,

This paper presents a study of the video compression effect on source camera identification based on the Photo-Response Non-Uniformity (PRNU). Specifically, the reliability of different types of frames in a compressed video is first investigated, which shows quantitatively that I-frames are more reliable than P-frames for PRNU estimation. Motivated by this observation, a new mechanism for estimating the reference PRNU and two mechanisms for estimating the test-video PRNU are proposed to achieve higher accuracy with fewer frames used.

Yuhong Liu (University of Rhode Island), “Security and Applications of Digital Trust and Reputation” (2012), Advisor: Prof. Yan Lindsay Sun

Cyber Competition has been recognized as an efficient way to facilitate research and education in cyber security Cyber Competition has been recognized as an efficient way to facilitate research and education in cyber security field [1]–[3]. We have discovered that the participants (i.e. players) in cyber competitions can cheat in order to gain a higher rank or collect more prizes. In this work, we use data collected from the CANT competition to analyze such cheating behaviors and propose to build a competition social network to detect cheating behaviors in cyber competitions.

We offer algorithms and visualization techniques for cyber trust in a Smart Grid system. Cyber trust is evaluated in terms of a mathematical model consisting of availability, detection and false alarm trust values, as well as a model of predictability. We develop a prototype Cyber Situational Awareness Visualization (CyberSAVe) tool to visualize cyber trust. We provide Operational Decision Aids (ODAs) displayed in context with a SCADA management information. We define cyber trust metrics, which are calculated and displayed in real-time in the Metric Assessment System (MAS) of CyberSAVe.

The security issue of complex networks has drawn significant concerns recently. While pure topological analyzes from a network security perspective provide some effective techniques, their inability to characterize the physical principles requires a more comprehensive model to approximate failure behavior of a complex network in reality. In this paper, based on an extended topological metric, we proposed an approach to examine the vulnerability of a specific type of complex network, i.e., the power system, against cascading failure threats.

Security issues in complex systems such as power grid, communication network, Internet, among others have attracted wide attention from academic, government and industry. In this paper, we investigate the vulnerabilities of power grid under a topology-based network model in the context of cascading failures caused by physical attacks against substations and transmission lines. In particular, we develop attack strategies from the attackers' points of view, aiming to cause severe damage to the network efficiency, as a way to revealing the vulnerability of the system.

The Internet has created vast opportunities to interact with strangers. The interactions can be fun, informative, and even profitable [1]. However, there is also risk involved. Will an eBay seller ship the product in time? Is the advice from a self-proclaimed expert on Epinion.com trustworthy? Does a product from Amazon.com have high quality as described?

The full version of the paper is available at http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6153140&tag=1

The vulnerability analysis is vital for safely running power grids. The simultaneous attack, which applies multiple failures simultaneously, does not consider the time domain in applying failures, and is limited to find unknown vulnerabilities of power grid networks. In this paper, we discover a new attack scenario, called the sequential attack, in which the failures of multiple network components (i.e., links/nodes) occur at different time. The sequence of such failures can be carefully arranged by attackers in order to maximize attack performances.

In the study of power grid security, the cascading failure analysis in multi-contingency scenarios has been a challenge due to its topological complexity and computational cost. Both network analyses and load ranking methods have their own limitations. In this paper, based on self-organizing map (SOM), we propose an integrated approach combining spatial feature (distance)-based clustering with electrical characteristics (load) to assess the vulnerability and cascading effect of multiple component sets in the power grid.