Digital forensics, computer forensics, cyber crime, computer crime The current study was a pilot study and attempted to add to the growing body of knowledge regarding inherent issues in computer forensics. The study consisted of an Internet based survey that asked respondents to identify the top five issues in computer forensics. 60 respondents answered the survey using a free form text field. The results indicated that education/training and certification were the most reported issue (18%) and lack of funding was the least reported (4%). These findings are consistent with a similar law enforcement community study (Stambaugh et al., 2001). The findings emphasize the fragmented nature of the computer forensics discipline. Currently there is a lack of a national framework for curricula and training development, and no gold standard for professional certification. The findings further support the criticism that there is a disproportional focus on the applied aspects of computer forensics, at the expense of the development of fundamental theories. Further implications of the findings are discussed as well as suggestions for future research in the area.

The most likely way for the world to be destroyed, most experts agree, is by accident. That’s where we come in; we’re computer professionals. We cause accidents.- Nathaniel Borenstein1 Q. So just put it in all perspective [sic]. What’s the worst-case power scenario, power we’re talking here – power lines, power grid? A. Absolute worst? I won’t even say absolute, but a very worst case could be loss of power for six months or more. Q. Over how big an area? A. Big as you want.- Frontline interview with power expert Joseph Weiss regarding the possible damage of a cyber attack on the power grid. 2

Abstract. Ever since the 9-11 incident, the multidisciplinary field of terrorism has experienced tremendous growth. As the domain has benefited greatly from recent advances in information technologies, more complex and challenging new issues have emerged from numerous counter-terrorism-related research communities as well as governments of all levels. In this paper, we describe an advanced knowledge discovery approach to addressing terrorism threats. We experimented with our approach in a project called Terrorism Knowledge Discovery Project that consists of several custom-built knowledge portals. The main focus of this project is to provide advanced methodologies for analyzing terrorism research, terrorists, and the terrorized groups (victims). Once completed, the system can also become a major learning resource and tool that the general community can use to heighten their awareness and understanding of global terrorism phenomenon, to learn how best they can respond to terrorism and, eventually, to garner significant grass root support for the government’s efforts to keep America safe. 1

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Much of the data that is collected and analyzed today is structural, consisting not only of entities but also of relationships between the entities. As a result, analysis applications rely on automated structural data mining approaches to find patterns and concepts of interest. This ability to analyze structural data has become a particular challenge in many security-related domains. In these domains, focusing on the relationships between entities in the data is critical to detect important underlying patterns. In this study we apply structural data mining techniques to automate analysis of nuclear smuggling data. In particular, we choose to model the data as a graph and use graph-based relational learning to identify patterns and concepts of interest in the data. In this article, we identify the analysis questions that are of importance to security analysts and describe the knowledge representation and data mining approach that we adopt for this challenge. We analyze the results using the Russian nuclear smuggling event database.

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www.elsevier.com/locate/cose The future of computer forensics: a needs analysis survey

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