Publication Details

Network Forensic Analysis for Lawful Enforcement Steroids, Distributed and Scalable

LETAVAY, V.; PLUSKAL, J.; RYŠAVÝ, O. Network Forensic Analysis for Lawful Enforcement Steroids, Distributed and Scalable. In Proceedings of the 6th Conference on the Engineering of Computer Based Systems (ECBS 2019), 2019. Bucharest: Association for Computing Machinery, 2019. p. 1-10. ISBN: 978-1-4503-7636-5.
Czech title
Síťová forenzní analýza pre vyšetrovací složky na steroidech, distribuovaná a škálovatelná
Type
conference paper
Language
English
Authors
URL
Keywords

Network Forensics, Network Traffic Processing, Distributed Computing

Abstract

Forensic analysis of intercepted network traffic focuses on finding and extracting communication evidence, such as instant messaging, email, VoIP calls, localization information, documents, images. Due to the amount of data captured, this process is time-consuming and complicated. Most commonly used forensic network analysis tools have limited capabilities for large data processing. In this paper, we are introducing a new tool that, through distributed processing, achieves better data processing performance using available computing resources. Thanks to the technology used, this tool can be used on commodity hardware in a local area network, in a dedicated computing cluster or cloud environment.

Published
2019
Pages
1–10
Proceedings
Proceedings of the 6th Conference on the Engineering of Computer Based Systems (ECBS 2019), 2019
ISBN
978-1-4503-7636-5
Publisher
Association for Computing Machinery
Place
Bucharest
DOI
UT WoS
000525376600020
EID Scopus
BibTeX
@inproceedings{BUT161452,
  author="Viliam {Letavay} and Jan {Pluskal} and Ondřej {Ryšavý}",
  title="Network Forensic Analysis for Lawful Enforcement Steroids, Distributed and Scalable",
  booktitle="Proceedings of the 6th Conference on the Engineering of Computer Based Systems (ECBS 2019), 2019",
  year="2019",
  pages="1--10",
  publisher="Association for Computing Machinery",
  address="Bucharest",
  doi="10.1145/3352700.3352720",
  isbn="978-1-4503-7636-5",
  url="https://dl.acm.org/citation.cfm?id=3352720"
}
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