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Author:

Tian Zhihong (Tian Zhihong.) | Jiang Wei (Jiang Wei.) | Li Yang (Li Yang.) | Dong Lan (Dong Lan.)

Indexed by:

Scopus SCIE CSCD

Abstract:

Network intrusion forensics is an important extension to present security infrastructure, and is becoming the focus of forensics research field. However, comparison with sophisticated multi-stage attacks and volume of sensor data, current practices in network forensic analysis are to manually examine, an error prone, labor-intensive and time consuming process. To solve these problems, in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments, and fuse digital evidence from different sources such as hosts and sub-networks automatically. In the end, we evaluate the method on well-known KDD Cup 1999 dataset. The results prove our method is very effective for real-time network forensics, and can provide comprehensible messages for a forensic investigators.

Keyword:

network forensics digital evidence security dempster-shafer theory fusion

Author Community:

  • [ 1 ] [Tian Zhihong]Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
  • [ 2 ] [Jiang Wei]Beijing Univ Technol, Coll Comp Sci, Beijing 100124, Peoples R China
  • [ 3 ] [Jiang Wei]Natl Univ Def Technol, Sch Comp, Changsha 410073, Hunan, Peoples R China
  • [ 4 ] [Li Yang]Haier Grp, Qingdao 266000, Peoples R China
  • [ 5 ] [Dong Lan]Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100029, Peoples R China

Reprint Author's Address:

  • [Tian Zhihong]Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China

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Source :

CHINA COMMUNICATIONS

ISSN: 1673-5447

Year: 2014

Issue: 5

Volume: 11

Page: 91-97

4 . 1 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:188

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 14

SCOPUS Cited Count: 20

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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