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2015-05-05
Lei Xu, Chunxiao Jiang, Jian Wang, Jian Yuan, Yong Ren.  2014.  Information Security in Big Data: Privacy and Data Mining. Access, IEEE. 2:1149-1176.

The growing popularity and development of data mining technologies bring serious threat to the security of individual,'s sensitive information. An emerging research topic in data mining, known as privacy-preserving data mining (PPDM), has been extensively studied in recent years. The basic idea of PPDM is to modify the data in such a way so as to perform data mining algorithms effectively without compromising the security of sensitive information contained in the data. Current studies of PPDM mainly focus on how to reduce the privacy risk brought by data mining operations, while in fact, unwanted disclosure of sensitive information may also happen in the process of data collecting, data publishing, and information (i.e., the data mining results) delivering. In this paper, we view the privacy issues related to data mining from a wider perspective and investigate various approaches that can help to protect sensitive information. In particular, we identify four different types of users involved in data mining applications, namely, data provider, data collector, data miner, and decision maker. For each type of user, we discuss his privacy concerns and the methods that can be adopted to protect sensitive information. We briefly introduce the basics of related research topics, review state-of-the-art approaches, and present some preliminary thoughts on future research directions. Besides exploring the privacy-preserving approaches for each type of user, we also review the game theoretical approaches, which are proposed for analyzing the interactions among different users in a data mining scenario, each of whom has his own valuation on the sensitive information. By differentiating the responsibilities of different users with respect to security of sensitive information, we would like to provide some useful insights into the study of PPDM.

2015-04-30
Ormrod, D..  2014.  The Coordination of Cyber and Kinetic Deception for Operational Effect: Attacking the C4ISR Interface. Military Communications Conference (MILCOM), 2014 IEEE. :117-122.

Modern military forces are enabled by networked command and control systems, which provide an important interface between the cyber environment, electronic sensors and decision makers. However these systems are vulnerable to cyber attack. A successful cyber attack could compromise data within the system, leading to incorrect information being utilized for decisions with potentially catastrophic results on the battlefield. Degrading the utility of a system or the trust a decision maker has in their virtual display may not be the most effective means of employing offensive cyber effects. The coordination of cyber and kinetic effects is proposed as the optimal strategy for neutralizing an adversary's C4ISR advantage. However, such an approach is an opportunity cost and resource intensive. The adversary's cyber dependence can be leveraged as a means of gaining tactical and operational advantage in combat, if a military force is sufficiently trained and prepared to attack the entire information network. This paper proposes a research approach intended to broaden the understanding of the relationship between command and control systems and the human decision maker, as an interface for both cyber and kinetic deception activity.