Conference item
Quantifying robustness of trust systems against collusive unfair rating attacks using information theory
- Abstract:
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Unfair rating attacks happen in existing trust and reputation systems, lowering the quality of the systems. There exists a formal model that measures the maximum impact of independent attackers [Wang et al., 2015] — based on information theory. We improve on these results in multiple ways: (1) we alter the methodology to be able to reason about colluding attackers as well, and (2) we extend the method to be able to measure the strength of any attacks (rather than just the strongest attack). U...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- International Joint Conferences on Artificial Intelligence
- Host title:
- Proceedings of the 24th International Joint Conference on Artificial Intelligence
- Journal:
- Proceedings of the 24th International Joint Conference on Artificial Intelligence More from this journal
- Pages:
- 111-117
- Publication date:
- 2015-09-25
- Acceptance date:
- 2015-04-16
- ISBN:
- 9781577357384
Item Description
- Keywords:
- Pubs id:
-
pubs:891856
- UUID:
-
uuid:c302e02d-e13b-4481-a40e-f5223d7e5101
- Local pid:
-
pubs:891856
- Source identifiers:
-
891856
- Deposit date:
-
2018-07-31
Terms of use
- Copyright holder:
- International Joint Conferences on Artificial Intelligence
- Copyright date:
- 2015
- Notes:
- Copyright © 2015 International Joint Conferences on Artificial Intelligence
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