Robustness of the MHITS Algorithm
{"Image DocumentName": "Robustness of the MHITS Algorithm", "Image ImageDescription": "Compromising techniques. Sybil attack [Douc02], Reputation theft, Whitewashing attack, etc. Compromising the input and the output of the algorithm. Sybil attack. Fundamental problem in online collaborative systems. A malicious user creates many fake accounts (Sybils) which all reference the user to boost his reputation (attacker\u2019s goal is to be higher up in the rankings) SybilGuard, SybilLimit are descentralized. SumUp is centralizerd. SybilGuard is based on the social network among user identities, where an edge between two identities indicates a human-established trust. relationship. Malicious users can create many identities but few trust relationships. Thus, there is a disproportionately-small cut in the graph between the sybil nodes and the honest nodes. SybilGuard exploits this property to bound the number of identities a malicious user can create. SybilLimit \u2013 leverages the same insight as SybilGuard but is an improved version that reduces the accepted Sybil nodes of a honest node from O(nlogn) to O(logn) for n honest nodes. When all nodes vote, SumUp leads to much lower attack capacity than SybilLimit despite the same asymptotic bound per attack edge. First, SumUp\u2019s bound of 1 + log n in. Theorem 5.1 is a loose upper bound of the actual average capacity. Second, since links pointing to lower-level. nodes are not eligible for ticket distribution, many incoming links of an adversarial nodes have zero tickets and thus. are assigned capacity of one. Countermeasures against Sybil attack. SybilGuard [YKGF06] SybilLimit [YGKX08] SumUp [TMLS09] Protocol type. Decentralized. Centralized. Accepted Sybils per attack edge.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}