Proposal / Submission Type
Peer Reviewed Paper
Location
Richmond, Virginia
Start Date
30-5-2012 3:20 PM
Abstract
Cloud Computing is becoming a significant technology trend nowadays, but its abrupt rise also creates a brand new front for cybercrime investigation with various challenges. One of the challenges is to track down infringing sharing of copyrighted content in cloud. To solve this problem, we study a typical type of content sharing technologies in cloud computing, analyze the challenges that the new technologies bring to forensics, formalize a procedure to get digital evidences and obtain analytical results based on the evidences to track down illegal uploader. Furthermore, we propose a reasoning model based on the probability distribution in a Bayesian Network to evaluate the analytical result of forensics examinations. The proposed method can accurately and scientifically track down the origin infringing content uploader and owner.
Keywords: cloud forensics, peer to peer, file sharing, tracking, CloudFront
Scholarly Commons Citation
He, Yi-Jun; Zhang, Echo P.; Hui, Lucas C.K.; Yiu, Siu Ming; and Chow, K.P., "Cloud Forensics Investigation: Tracing Infringing Sharing of Copyrighted Content in Cloud" (2012). Annual ADFSL Conference on Digital Forensics, Security and Law. 13.
https://commons.erau.edu/adfsl/2012/wednesday/13
Included in
Computer Engineering Commons, Computer Law Commons, Electrical and Computer Engineering Commons, Forensic Science and Technology Commons, Information Security Commons
Cloud Forensics Investigation: Tracing Infringing Sharing of Copyrighted Content in Cloud
Richmond, Virginia
Cloud Computing is becoming a significant technology trend nowadays, but its abrupt rise also creates a brand new front for cybercrime investigation with various challenges. One of the challenges is to track down infringing sharing of copyrighted content in cloud. To solve this problem, we study a typical type of content sharing technologies in cloud computing, analyze the challenges that the new technologies bring to forensics, formalize a procedure to get digital evidences and obtain analytical results based on the evidences to track down illegal uploader. Furthermore, we propose a reasoning model based on the probability distribution in a Bayesian Network to evaluate the analytical result of forensics examinations. The proposed method can accurately and scientifically track down the origin infringing content uploader and owner.
Keywords: cloud forensics, peer to peer, file sharing, tracking, CloudFront
