Large Scale Graph Based Network Forensics Analysis

In this paper we tackle the problem of performing graph based network forensics analysis at a large scale. To this end, we propose a novel distributed version of a popular network forensics analysis algorithm, the one by Wang and Daniels [18]. Our version of the Wang and Daniels algorithm has been f...

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Bibliographic Details
Published inPattern Recognition. ICPR International Workshops and Challenges Vol. 12665; pp. 457 - 469
Main Authors Di Rocco, Lorenzo, Petrillo, Umberto Ferraro, Palini, Francesco
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2021
Springer International Publishing
SeriesLecture Notes in Computer Science
Online AccessGet full text
ISBN3030688208
9783030688202
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-68821-9_39

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Summary:In this paper we tackle the problem of performing graph based network forensics analysis at a large scale. To this end, we propose a novel distributed version of a popular network forensics analysis algorithm, the one by Wang and Daniels [18]. Our version of the Wang and Daniels algorithm has been formulated according to the MapReduce paradigm and implemented using the Apache Spark framework. The resulting code is able to analyze in a scalable way graphs of arbitrary size thanks to its distributed nature. We also present the results of an experimental study where we assessed both the time performance and the scalability of our algorithm when run on a distributed system of increasing size.
ISBN:3030688208
9783030688202
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-68821-9_39