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  • 标题:Optimizing Live Digital Evidence Mining Using Structural Subroutines of Apriori Algorithm
  • 本地全文:下载
  • 作者:Akshay Zadgaonkar ; Ms. Vijaya Balpande
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:04
  • 页码:1399-1405
  • 出版社:Engg Journals Publications
  • 摘要:The Scope and Complexity of the Internet has grown exponentially. This growth has made digital forensic investigation a very challenging task. Even the modest intra-organizational networks have sufficient network traffic to pose a problem for digital crime investigators to police and collect evidences. Another problem in Network based Crime Investigation is that Offline Mining Techniques do not yield pervasive evidence. At the same time due to voluminous traffic, live evidence mining becomes a challenge. This paper presents a technique to optimize the live evidence mining by using the principles of apriori algorithm to trigger the evidence collection mechanism at right and opportune moment. The crux of this technique is answering �When & What Information� to Collect about a subject of investigation or Data.
  • 关键词:Evidence Mining;Live Forensics;Aprori
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