Abstract
Collaborative Intrusion Detection Systems (CIDSs) are an emerging field in cyber-security. In such an approach, multiple sensors collaborate by exchanging alert data with the goal of generating a complete picture of the monitored network. This can provide significant improvements in intrusion detection and especially in the identification of sophisticated attacks. However, the challenge of deciding to which extend a sensor can trust others, has not yet been holistically addressed in related work. In this paper, we firstly propose a set of requirements for reliable trust management in CIDSs. Afterwards, we carefully investigate the most dominant CIDS trust schemes. The main contribution of the paper is mapping the results of the analysis to the aforementioned requirements, along with a comparison of the state of the art. Furthermore, this paper identifies and discusses the research gaps and challenges with regard to trust and CIDSs.
Original language | English |
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Title of host publication | Trust Management XI - 11th IFIP WG 11.11 International Conference, IFIPTM 2017, Proceedings |
Editors | Jan-Philipp Steghofer, Babak Esfandiari |
Number of pages | 16 |
Publisher | Springer Publishing Company |
Publication date | 2017 |
Pages | 94-109 |
ISBN (Print) | 9783319591704 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Event | 11th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2017 - Gothenburg, Sweden Duration: 12 Jun 2017 → 16 Jun 2017 |
Conference
Conference | 11th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2017 |
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Country/Territory | Sweden |
City | Gothenburg |
Period | 12/06/2017 → 16/06/2017 |
Series | I F I P Advances in Information and Communication Technology |
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Volume | 505 |
ISSN | 1868-4238 |
Bibliographical note
Funding Information:This work has received funding from the European Union’s Horizon 2020 Research and Innovation Program, PROTECTIVE, under Grant Agreement No 700071.
Publisher Copyright:
© IFIP International Federation for Information Processing 2017.