Read e-book online Computational Intelligence in Digital Forensics: Forensic PDF

By Azah Kamilah Muda, Yun-Huoy Choo, Ajith Abraham, Sargur N. Srihari

ISBN-10: 3319058843

ISBN-13: 9783319058849

ISBN-10: 3319058851

ISBN-13: 9783319058856

Computational Intelligence ideas were broadly explored in a number of domain names together with forensics. research in forensic encompasses the learn of development research that resolution the query of curiosity in defense, clinical, felony, genetic reviews and and so on. although, forensic research is mostly played via experiments in lab that's dear either in rate and time. accordingly, this publication seeks to discover the growth and development of computational intelligence approach in numerous concentration components of forensic experiences. This goals to construct greater connection among desktop scientists and forensic box experts.

This publication, Computational Intelligence inDigital Forensics: Forensic research and Applications, is the 1st quantity within the clever structures Reference Library sequence. The publication provides unique study effects and leading edge functions of computational intelligence in electronic forensics. This edited quantity comprises seventeen chapters and offers the newest state of the art development of Computational Intelligence in electronic Forensics; in either theoretical and alertness papers concerning novel discovery in clever forensics. The chapters are extra prepared into 3 sections: (1) creation, (2) Forensic Discovery and research, which discusses the computational intelligence applied sciences hired in electronic Forensic, and (3) clever Forensic technological know-how functions, which encompasses the purposes of computational intelligence in electronic Forensic, reminiscent of human anthropology, human biometrics, human via items, medications, and digital devices.

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Extra info for Computational Intelligence in Digital Forensics: Forensic Investigation and Applications

Sample text

Also, finding trends and frequent (interesting) patterns through SNs is another useful task of SNM techniques for analyzing SNs [98, 99]. Mining communities and graph patterns - as two methodologies - in SNs are also could be used in pattern mining to find (repetitive/periodical) behaviors. In a general view, content (text, multimedia), structure and relationships between people (account) could be the subject of mining to extract pieces of evidence and facts for analysis purposes. 3 Visualization A good starting point for the analysis process is to map (criminals/illegal/abnormal) activities to the visualized graph that displays associations and relationships between the acts and individuals.

The authors discussed recent advances in the study of human dynamics for multimedia social networks and reviewed a few methodologies to investigate impact of human factors on multimedia security from a signal processing perspective. Also, a framework was also presented for modeling and analyzing user behaviors. 34 M. Keyvanpour, M. Moradi, and F. Hasanzadeh Authors of [3, 4] proposed some SNF tools that could be used to help in investigation of social network site crimes and raise user awareness.

Thus, there are several studies that have been devoted to analyzing criminal and terrorist SNs like [79, 80, 81, 82, 83, 84]. g. for terrorist networks- could be depicted as follows: Interrelationships are displayed through graphs. Graphs are built by analyzing the data including nodes (terrorists) and links (relationships). Then, these relationships are used to understand information about people and group [78]. SNA has different forms such as Social Networks Mining (SNM), monitoring, etc. 1 Monitoring SN monitoring for observing users’ interactions, connections and behaviors is a supervisory task that comes in handy in different applications like checking kids about using SNSs and so on.

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Computational Intelligence in Digital Forensics: Forensic Investigation and Applications by Azah Kamilah Muda, Yun-Huoy Choo, Ajith Abraham, Sargur N. Srihari

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