Due to the open, anonymous nature of many P2P networks, new identities- or sybils- may be created cheaply and in large numbers. Given a reputation system, a peer may attempt to falsely raise its reputation by creating fake links between its sybils. Many existing reputation mechanisms are not resistant to these types of strategies. Using a static graph formulation of reputation, we attempt to formalize the notion of sybilproofness. We show that there is no symmetric sybilproof reputation function. For nonsymmetric reputations, following the notion of reputation propagation along paths, we give a general asymmetric reputation function based on flow and give conditions for sybilproofness.

The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes. We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes. We are currently developing a system within this framework where we employ a Bayesian formulation, specifically a beta reputation system, for reputation representation, updates and integration. We will explain the reasoning behind our design choices, analyzing their pros & cons. We conclude the paper by verifying the efficacy of this system through some preliminary simulation results.

1 Introduction Establishing trust is a fundamental problem in distributedsystems. Peer-to-peer systems, in which service functionality is distributed across clients, eliminate the cen-tralized components that have traditionally functioned as de facto trust brokers, and consequently exacerbate trust-related problems. When peers lack meaningful measures on which to base trust decisions, they end up receivingservices from untrustworthy peers, with e ffects that canrange from wasted resources on mislabeled content to

An emerging paradigm in peer-to-peer (P2P) networks is to explicitly consider incentives as part of the protocol design in order to promote good (or discourage bad) behavior. However, effective incentives are hampered by the challenges of a P2P environment, e.g. transient users and no central authority. In this paper, we quantify these challenges, reporting the results of a month-long measurement of millions of users of the BitTorrent file sharing system. Surprisingly, given BitTorrent’s popularity, we identify widespread performance and availability problems. These measurements motivate the design and implementation of a new, one hop reputation protocol for P2P networks. Unlike digital currency systems, where contribution information is globally visible, or titfor-tat, where no propagation occurs, one hop reputations limit propagation to at most one intermediary. Through trace-driven analysis and measurements of a deployment on PlanetLab, we find that limited propagation improves performance and incentives relative to BitTorrent. 1

Abstract—We consider the design of bandwidth-demanding broadcasting applications using overlays in environments characterized by hosts with limited and asymmetric bandwidth, and significant heterogeneity in upload bandwidth. Such environments are critical to consider to extend the applicability of overlay multicast to mainstream Internet environments where insufficient bandwidth exists to support all hosts, but have not received adequate attention from the research community. We leverage the multitree framework and design heuristics to enable it to consider host contribution and operate in bandwidth-scarce environments. Our extensions seek to simultaneously achieve good utilization of system resources, performance to hosts commensurate to their contributions, and consistent performance. We have implemented the system and conducted an Internet evaluation on PlanetLab using real traces from previous operational deployments of an overlay broadcasting system. Our results indicate for these traces, our heuristics can improve the performance of high contributors by 10–240 % and facilitate equitable bandwidth distribution among hosts with similar contributions. Index Terms—Bandwidth detection, incentive, multitree, overlay multicast, NAT, saturation detection.

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.

Peer-to-peer filesharing is now commonplace and its traffic now dominates bandwidth consumption at many Internet peering points. Recent studies indicate that much of this filesharing activity involves corrupt and polluted files. This paper describes Credence, a new object-based reputation system, and shows how it can counteract content pollution in peer-to-peer filesharing networks. Credence allows honest peers to assess the authenticity of online content by securely tabulating and managing endorsements from other peers. We employ a novel voter correlation scheme to weigh the opinions of peers, which gives rise to favorable incentives and system dynamics. We present simulation results indicating that our system is scalable, efficient, and robust.

Abstract. Without trust, pervasive devices cannot collaborate effectively, and without collaboration, the pervasive computing vision cannot be made a reality. Distributed trust frameworks may support trust and thus foster collaboration in an hostile pervasive computing environment. Existing frameworks deal with foundational properties of computational trust. We here propose a distributed trust framework that satisfies a broader range of properties. Our framework: (i) evolves trust based on a Bayesian formalization, whose trust metric is expressive, yet tractable; (ii) is lightweight; (iii) protects user anonymity, whilst being resistant to “Sybil attacks ” (and enhancing detection of two collusion attacks); (iv) integrates a risk-aware decision module. We evaluate the framework through four experiments. 1

People living in urban areas spend a considerable amount of time on public transport, for example, commuting to/from work. During these periods, opportunities for inter-personal networking present themselves, as many members of the public now carry electronic devices equipped with Bluetooth or other wireless technology. Using these devices, individuals can share content (e.g., music, news and video clips) with fellow travellers that are on the same train or bus. Transferring media content takes time; in order to maximise the chances of successful downloads, users should identify neighbours that possess desirable content and who will travel with them for long-enough periods. In this paper, we propose a user-centric prediction scheme that collects historical colocation information to determine the best content sources. The scheme works on the assumption that people have a high degree of regularity in their movements. We first validate this assumption on a real dataset, that consists of traces of people moving in a large city’s mass transit system. We then demonstrate experimentally on these traces that our prediction scheme significantly improves communication efficiency, when compared to a memory(history)-less source selection scheme.

Peer-to-Peer (P2P) reputation systems are essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest, and malicious peer behaviors. The system collects locally-generated peer feedbacks and aggregates them to yield the global reputation scores. Surprisingly, most previous work ignored the distribution of peer feedbacks. We use a trust overlay network (TON) to model the trust relationships among peers. After examining the eBay transaction trace of over 10,000 users, we discovered a power-law distribution in user feedbacks. Our mathematical analysis justifies that power-law distribution is applicable to any dynamically growing P2P systems, either structured or unstructured. We develop a robust and scalable P2P reputation system, PowerTrust, to leverage the power-law feedback characteristics. The PowerTrust system dynamically selects small number of power nodes that are most reputable using a distributed ranking mechanism. By using a look-ahead random walk strategy and leveraging the power nodes, the PowerTrust significantly improves in global reputation accuracy and aggregation speed. PowerTrust is adaptable to dynamics in peer joining and leaving and robust to disturbance by malicious peers. Through P2P network simulation experiments, we find significant performance gains in using PowerTrust. This power-law guided reputation system design proves to achieve high query success rate in P2P file-sharing applications. The system also reduces the total job makespan and failure rate in large-scale, parameter-sweeping P2P Grid applications.