Download Advances in Digital Forensics X: 10th IFIP WG 11.9 by Gilbert Peterson, Sujeet Shenoi PDF

By Gilbert Peterson, Sujeet Shenoi

Digital forensics offers with the purchase, renovation, exam, research and presentation of digital proof. Networked computing, instant communications and transportable digital units have accelerated the position of electronic forensics past conventional laptop crime investigations. virtually each crime now consists of a few point of electronic proof; electronic forensics presents the options and instruments to articulate this proof. electronic forensics additionally has myriad intelligence functions. additionally, it has a necessary function in info coverage -- investigations of safety breaches yield beneficial details that may be used to layout safer structures. Advances in electronic Forensics X describes unique learn effects and cutting edge purposes within the self-discipline of electronic forensics. moreover, it highlights a number of the significant technical and felony concerns relating to electronic proof and digital crime investigations. The components of assurance comprise: - net Crime Investigations; - Forensic innovations; - cellular equipment Forensics; - Forensic instruments and coaching. This booklet is the tenth quantity within the annual sequence produced via the foreign Federation for info Processing (IFIP) operating team 11.9 on electronic Forensics, a global group of scientists, engineers and practitioners devoted to advancing the state-of-the-art of analysis and perform in electronic forensics. The e-book includes a collection of twenty-two edited papers from the tenth Annual IFIP WG 11.9 overseas convention on electronic Forensics, held in Vienna, Austria within the wintry weather of 2014. Advances in electronic Forensics X is a crucial source for researchers, school individuals and graduate scholars, in addition to for practitioners and members engaged in learn and improvement efforts for the legislation enforcement and intelligence communities.

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The relationships between offender behavior and personal characteristics are also examined. The results yield a taxonomy of online auction fraud offenders: (i) novice-moderatelyactive; (ii) intermediate-inactive; and (iii) experienced-active. 6% accurate identification of the offender type. The results demonstrate that (intrinsic) personal motivation, education level and age are the most significant characteristics of experienced-active offenders. Keywords: Online auctions, criminal profiling, multivariate behavioral analysis 1.

Selecting terms based on their information gain produces more accurate results. In this case, IG-based feature selection retained the top 10,000 terms from the IRC data collection. 5 Classification The SVM-Light classifier [7] from the Weka toolkit [15] was used as the classifier. 5 decision tree). Figure 2 presents an overview of the classification process. The initial stage involved the preprocessing of text as in the training phase. Following this, the data was transformed to a vector space model.

1 Combination Similarity (a) Classification precision. (b) Classification recall. 3 Combination Similarity (c) Number of clusters. Figure 4. 3 Combination Similarity (d) Classification F1 -measure. Classification performance of document selection IRC channels. While single-link clustering reduces the number of clusters for the given similarity values more rapidly, it produces a significant accuracy loss. In contrast, complete-link clustering can reduce the number of needed training samples to less than 40% with minimal loss of recall.

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