
In this paper, we propose a reputation management scheme for partially decentralized peer-to-peer systems. The reputation scheme helps to build trust among peers based on their past experiences and feedback from other peers. Two selection advisor algorithms are proposed for helping peers to select the most trustworthy peer to download from. The proposed algorithms can detect malicious peers sending inauthentic files. The Malicious detector algorithm is also proposed to detect liar peers that send the wrong feedback to subvert the reputation system. The new concept of suspicious transactions is introduced and explained. Simulation results confirm the capability of the proposed algorithms to effectively detect malicious peers and isolate them from the system, hence reducing the amount of inauthentic uploads, increasing peers' satisfaction, and preserving network resources.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 41 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
