Optimizing Live Digital Evidence Mining Using Structural Subroutines of Apriori Algorithm

Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 4

Abstract

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.

Authors and Affiliations

Akshay Zadgaonkar , Ms. Vijaya Balpande

Keywords

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  • EP ID EP134595
  • DOI -
  • Views 67
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How To Cite

Akshay Zadgaonkar, Ms. Vijaya Balpande (2011). Optimizing Live Digital Evidence Mining Using Structural Subroutines of Apriori Algorithm. International Journal on Computer Science and Engineering, 3(4), 1399-1405. https://europub.co.uk/articles/-A-134595