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Expanded version of the Guest Editorial
for Special Issue on Signal Processing for Art Investigation
(IEEE Signal Processing Magazine, July 2015)

Include short summaries for each of the 11 articles in the special issue.

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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,

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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.

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

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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.

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