By Nicolai Kuntze, Carsten Rudolph, Aaron Alva, Barbara Endicott-Popovsky (auth.), Gilbert Peterson, Sujeet Shenoi (eds.)
Digital forensics offers with the purchase, protection, exam, research and presentation of digital proof. Networked computing, instant communications and transportable digital units have elevated the position of electronic forensics past conventional machine crime investigations. virtually each crime now includes a few element of electronic proof; electronic forensics offers the recommendations and instruments to articulate this facts. electronic forensics additionally has myriad intelligence functions. additionally, it has a necessary position in details insurance -- investigations of safety breaches yield precious info that may be used to layout safer platforms. Advances in electronic Forensics VIII describes unique learn effects and cutting edge functions within the self-discipline of electronic forensics. additionally, it highlights a number of the significant technical and felony matters relating to electronic proof and digital crime investigations. The parts of assurance comprise: topics and concerns, forensic innovations, cellular phone forensics, cloud forensics, community forensics, and complicated forensic ideas. This ebook is the 8th quantity within the annual sequence produced by way of the foreign Federation for info Processing (IFIP) operating staff 11.9 on electronic Forensics, a global group of scientists, engineers and practitioners devoted to advancing the state-of-the-art of study and perform in electronic forensics. The e-book encompasses a collection of twenty-two edited papers from the 8th Annual IFIP WG 11.9 overseas convention on electronic Forensics, held on the collage of Pretoria, Pretoria, South Africa within the spring of 2012. Advances in electronic Forensics VIII is a vital source for researchers, school participants and graduate scholars, in addition to for practitioners and participants engaged in learn and improvement efforts for the legislations enforcement and intelligence groups. Gilbert Peterson is an affiliate Professor of laptop Engineering on the Air strength Institute of expertise, Wright-Patterson Air strength Base, Ohio, united states. Sujeet Shenoi is the F.P. Walter Professor of desktop technology and a Professor of Chemical Engineering on the collage of Tulsa, Tulsa, Oklahoma, USA.
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Extra resources for Advances in Digital Forensics VIII: 8th IFIP WG 11.9 International Conference on Digital Forensics, Pretoria, South Africa, January 3-5, 2012, Revised Selected Papers
Fn and G = g1 g2 . . gm (n ≤ m), a similarity distance SD(F, G) is deﬁned as: 1 SD(F, G) = N n max D(fi , gj ). m In other words, for each ﬁlter of the shorter digest F , the best match in G is found and the maxima are averaged to produce the ﬁnal result. In the special case where F has a single ﬁlter, the result is the best match, which is the expected behavior. In the case where the two digests have a comparable number of ﬁlters, the similarity distance estimates their highest similarity.
6. Conclusions The similarity-digest-based approach presented in this paper can efﬁciently correlate large forensic data sets at the byte-stream level. This 32 ADVANCES IN DIGITAL FORENSICS VIII enables content ﬁltering to be applied on a wide scale and the ﬁltering to be incorporated early in the forensic process. Current best practices dictate that the creation of a cloned copy of the original media, such as a hard drive, is the ﬁrst step in a formal investigation. However, it is usually the case that no useful processing is done during this lengthy task and, at the end of the task, the investigators know almost nothing more than they did at the beginning of the task.
13] H. Pucha, D. Andersen and M. Kaminsky, Exploiting similarity for multi-source downloads using ﬁle handprints, Proceedings of the Fourth USENIX Symposium on Networked Systems Design and Implementation, pp. 15–28, 2007.  M. Rabin, Fingerprinting by Random Polynomials, Technical Report TR1581, Center for Research in Computing Technology, Harvard University, Cambridge, Massachusetts, 1981.  V. Roussev, Hashing and data ﬁngerprinting in digital forensics, IEEE Security and Privacy, vol.