A survey of attack and defense techniques for reputation systems

Abstract

Reputation systems provide mechanisms to produce a metric encapsulating reputation for a given domain for each identity within the system. These systems seek to generate an accurate assessment in the face of various factors including but not limited to unprecedented community size and potentially adversarial environments.We focus on attacks and defense mechanisms in reputation systems. We present an analysis framework that allows for general decomposition of existing reputation systems. We classify attacks against reputation systems by identifying which system components and design choices are the target of attacks. We survey defense mechanisms employed by existing reputation systems. Finally, we analyze several landmark systems in the peer-to-peer domain, characterizing their individual strengths and weaknesses. Our work contributes to understanding 1) which design components of reputation systems are most vulnerable, 2) what are the most appropriate defense mechanisms and 3) how these defense mechanisms can be integrated into existing or future reputation systems to make them resilient to attacks.

Tracking freeriders in gossip-based content dissemination systems

“…In addition, one can limit the number of nodes a node can accuse (per minute); this would have a limited effect on legitimate accusations provided that the proportion of freeriders remains low. Other existing solutions (e.g., [40], see [24] for a comprehensive survey) propose to modulate accusations by the credibility/trustworthiness (which can be the reputation of the node itself) of the accusing node. More complex solutions can be used; for instance in SumUp [54], the nodes propagate their accusations (i.e., votes in the original version) along the edges of a social network in order to mitigate the effect of a coalition of related nodes that try to jointly wrongfully accuse other nodes.…”

A Reputation System for Multirole Sessions

“…We refer to existing surveys [15,14,11] for a general introduction to reputation systems. It is interesting to notice that the reputation system associated with our calculus can be classified, according to [15], as a non-probabilistic experiencebased system, where principals are evaluated by inspecting their history, which is built by recording their past interaction with other principals.…”

SocialFilter: Introducing social trust to collaborative spam mitigation

“…SocialFilter is inspired by prior work on reputation and trust management systems [14]. Well-known trust and reputation management systems include the rating scheme used by the eBay on-line auction site, object reputation systems for P2P file sharing networks [15,25] and PageRank [8].…”