How to Use Information Theory to Mitigate Unfair Rating Attacks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

How to Use Information Theory to Mitigate Unfair Rating Attacks

Résumé

In rating systems, users want to construct accurate opinions based on ratings. However, the accuracy is bounded by the amount of information transmitted (leaked) by ratings. Rating systems are susceptible to unfair rating attacks. These attacks may decrease the amount of leaked information, by introducing noise. A robust trust system attempts to mitigate the effects of these attacks on the information leakage. Defenders cannot influence the actual ratings: being honest or from attackers. There are other ways for the defenders to keep the information leakage high: blocking/selecting the right advisors, observing transactions and offering more choices. Blocking suspicious advisors can only decrease robustness. If only a limited number of ratings can be used, however, then less suspicious advisors are better, and in case of a tie, newer advisors are better. Observing transactions increases robustness. Offering more choices may increase robustness.
Fichier principal
Vignette du fichier
428098_1_En_2_Chapter.pdf (326.65 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01438346 , version 1 (17-01-2017)

Licence

Paternité

Identifiants

Citer

Tim Muller, Dongxia Wang, Yang Liu, Jie Zhang. How to Use Information Theory to Mitigate Unfair Rating Attacks. 10th IFIP International Conference on Trust Management (TM), Jul 2016, Darmstadt, Germany. pp.17-32, ⟨10.1007/978-3-319-41354-9_2⟩. ⟨hal-01438346⟩
65 Consultations
100 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More