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Taxonomy and Survey of Collaborative Intrusion Detection

Published: 11 May 2015 Publication History

Abstract

The dependency of our society on networked computers has become frightening: In the economy, all-digital networks have turned from facilitators to drivers; as cyber-physical systems are coming of age, computer networks are now becoming the central nervous systems of our physical world—even of highly critical infrastructures such as the power grid. At the same time, the 24/7 availability and correct functioning of networked computers has become much more threatened: The number of sophisticated and highly tailored attacks on IT systems has significantly increased. Intrusion Detection Systems (IDSs) are a key component of the corresponding defense measures; they have been extensively studied and utilized in the past. Since conventional IDSs are not scalable to big company networks and beyond, nor to massively parallel attacks, Collaborative IDSs (CIDSs) have emerged. They consist of several monitoring components that collect and exchange data. Depending on the specific CIDS architecture, central or distributed analysis components mine the gathered data to identify attacks. Resulting alerts are correlated among multiple monitors in order to create a holistic view of the network monitored. This article first determines relevant requirements for CIDSs; it then differentiates distinct building blocks as a basis for introducing a CIDS design space and for discussing it with respect to requirements. Based on this design space, attacks that evade CIDSs and attacks on the availability of the CIDSs themselves are discussed. The entire framework of requirements, building blocks, and attacks as introduced is then used for a comprehensive analysis of the state of the art in collaborative intrusion detection, including a detailed survey and comparison of specific CIDS approaches.

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      cover image ACM Computing Surveys
      ACM Computing Surveys  Volume 47, Issue 4
      July 2015
      573 pages
      ISSN:0360-0300
      EISSN:1557-7341
      DOI:10.1145/2775083
      • Editor:
      • Sartaj Sahni
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      Publication History

      Published: 11 May 2015
      Accepted: 01 January 2015
      Revised: 01 November 2014
      Received: 01 February 2014
      Published in CSUR Volume 47, Issue 4

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      Author Tags

      1. Collaborative intrusion detection
      2. attacks
      3. classification
      4. network security

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