By Gilbert Peterson, Sujeet Shenoi
Digital forensics offers with the purchase, upkeep, exam, research and presentation of digital proof. Networked computing, instant communications and transportable digital units have extended the position of electronic forensics past conventional machine crime investigations. essentially each crime now contains a few element of electronic proof; electronic forensics offers the thoughts and instruments to articulate this proof. electronic forensics additionally has myriad intelligence purposes. in addition, it has an important function in info insurance -- investigations of defense breaches yield helpful details that may be used to layout safer platforms. Advances in electronic Forensics X describes unique study effects and leading edge purposes within the self-discipline of electronic forensics. additionally, it highlights many of the significant technical and felony concerns regarding electronic facts and digital crime investigations. The parts of insurance contain: - web Crime Investigations; - Forensic suggestions; - cellular equipment Forensics; - Forensic instruments and coaching. This e-book is the tenth quantity within the annual sequence produced through the overseas Federation for info Processing (IFIP) operating crew 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 publication encompasses a number of twenty-two edited papers from the tenth Annual IFIP WG 11.9 foreign convention on electronic Forensics, held in Vienna, Austria within the wintry weather of 2014. Advances in electronic Forensics X is a vital source for researchers, school participants and graduate scholars, in addition to for practitioners and members engaged in examine and improvement efforts for the legislation enforcement and intelligence communities.
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Additional info for Advances in Digital Forensics X: 10th IFIP WG 11.9 International Conference, Vienna, Austria, January 8-10, 2014, Revised Selected Papers
Conclusions The use of fraud trees to analyze Internet credit card fraud can systematically provide an obstacle to each type of fraud proactively before the fraud method is known. By including obstacle formation and transformation, fraud trees are more reﬁned than attack trees and adopt a diﬀerent perspective compared with goal trees. An interesting aspect is that a priori knowledge of the branches of the fraud tree occupied by a transaction is required because the tree includes countermeasures to deal with each type of fraud.
Edge, al.  have employed a protection tree in an investigation of an online banking system to defeat various fraudulent methods modeled in the corresponding attack tree. The approach is extended in this paper by placing fraud methods and the corresponding protection measures in the same tree to clarify the relationship between fraud methods and fraud protection. 1 Goal Trees The speciﬁcation language of the KAOS framework has four domains: goal, operation, object and responsibility. This paper analyzes credit 19 Blackwell card fraud in the goal domain.
Classifier Training Learned Model Classifier Model Training process. In the classiﬁcation process, a “document” is assumed to be an IRC chatroom or a web forum (thread), and “terms” are the words in IRC messages or web forum posts. The terms are mapped from each document to a numeric vector via the bag of words (BoW) model . This model is agnostic to the exact ordering of terms within a document and interprets the terms as a set for each document. The resulting vector space model allows diﬀerent weightings of the frequencies of individual terms.
Advances in Digital Forensics X: 10th IFIP WG 11.9 International Conference, Vienna, Austria, January 8-10, 2014, Revised Selected Papers by Gilbert Peterson, Sujeet Shenoi