In peer-to-peer systems, attrition attacks include both traditional, network-level denial of service attacks as well as application-level attacks in which malign peers conspire to waste loyal peers' resources. We describe several defenses for LOCKSS, a peer-to-peer digital preservation system, that help ensure that application-level attacks even from powerful adversaries are less effective than simple network-level attacks, and that network-level attacks must be intense, wide-spread, and prolonged to impair the system.
. Some researchers have proposed storing useless content in exchange for having content be stored as a way to enforce symmetric storage relationships. Compliance enforcement is achieved by asking the peer storing the file of interest to hash some portion of the file as proof that it is still storing the file @cite_42 @cite_37 .
@cite_37 @cite_42
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Peer-to-peer storage systems assume that their users consume resources in proportion to their contribution. Unfortunately, users are unlikely to do this without some enforcement mechanism. Prior solutions to this problem require centralized infrastructure, constraints on data placement, or ongoing administrative costs. All of these run counter to the design philosophy of peer-to-peer systems.Samsara enforces fairness in peer-to-peer storage systems without requiring trusted third parties, symmetric storage relationships, monetary payment, or certified identities. Each peer that requests storage of another must agree to hold a claim in return---a placeholder that accounts for available space. After an exchange, each partner checks the other to ensure faithfulness. Samsara punishes unresponsive nodes probabilistically. Because objects are replicated, nodes with transient failures are unlikely to suffer data loss, unlike those that are dishonest or chronically unavailable. Claim storage overhead can be reduced when necessary by forwarding among chains of nodes, and eliminated when cycles are created. Forwarding chains increase the risk of exposure to failure, but such risk is modest under reasonable assumptions of utilization and simultaneous, persistent failure. We propose a privacy protection framework for large-scale content-based information retrieval. It offers two layers of protection. First, robust hash values are used as queries to prevent revealing original content or features. Second, the client can choose to omit certain bits in a hash value to further increase the ambiguity for the server. Due to the reduced information, it is computationally difficult for the server to know the client’s interest. The server has to return the hash values of all possible candidates to the client. The client performs a search within the candidate list to find the best match. Since only hash values are exchanged between the client and the server, the privacy of both parties is protected. We introduce the concept oftunable privacy, where the privacy protection level can be adjusted according to a policy. It is realized through hash-based piecewise inverted indexing. The idea is to divide a feature vector into pieces and index each piece with a subhash value. Each subhash value is associated with an inverted index list. The framework has been extensively tested using a large image database. We have evaluated both retrieval performance and privacy-preserving performance for a particular content identification application. Two different constructions of robust hash algorithms are used. One is based on random projections; the other is based on the discrete wavelet transform. Both algorithms exhibit satisfactory performance in comparison with state-of-the-art retrieval schemes. The results show that the privacy enhancement slightly improves the retrieval performance. We consider the majority voting attack for estimating the query category and identification. Experiment results show that this attack is a threat when there are near-duplicates, but the success rate decreases with the number of omitted bits and the number of distinct items. In a Peer-to-Peer (P2P) file-sharing system, a node finds and retrieves its desired file. If multiple nodes cache the same file to provide others, we can achieve a dependable file-sharing system with low latency and high file availability. However, a node has to spend costs, e.g., processing load or storage capacity, on caching a file. Consequently, a node may selfishly behave and hesitate to cache a file. In such a case, unpopular files are likely to disappear from the system. In this paper, we aim to reveal whether effective caching in the whole system emerges from autonomous and selfish node behavior. We discuss relationship between selfish node behavior and system dynamics by using evolutionary game theory. Through theoretic analysis, we show that a file-sharing system can be robust to file disappearance depending on a cost and demand model for caching even if nodes behave selfishly. Furthermore, we also conduct several simulation-based analysis in terms of network structures, evolving network, load balancing, and system stability. As a result, we demonstrate that a file-sharing system with good properties, i.e., robustness to file disappearance, low search latency, well load-balancing, and high stability, can be achieved independent of network structures and dynamics. In this paper we propose a new Peer-to-Peer architecture for a censorship resistant system with user, server and active-server document anonymity as well as efficient document retrieval. The retrieval service is layered on top of an existing Peer-to-Peer infrastructure, which should facilitate its implementation. The key idea is to separate the role of document storers from the machines visible to the users, which makes each individual part of the system less prone to attacks, and therefore to censorship.