移动P2P分布式信任模型设计

移动P2P网络的开放性和松耦合特性使得节点恶意攻击行为普遍存在,而现有基于声誉的信任模型大都基于“信誉值高的节点评价推荐越可信”的假设,无法识别恶意节点动态策略性攻击行为。针对这一问题,将社会网络相关理论引入信任系统,提出一种基于社会距离的信任模型（SD2Trust）。该模型区分了服务可信度和推荐评价可信度,用多维结构同型性描述向量刻画节点网络地位和行为特征,根据社会距离确定推荐节点集和推荐信誉计算权重,综合信任考虑了诋毁风险。理论分析和实验结果表明,该模型能有效对抗恶意节点动态策略攻击行为。     

P2P文件共享系统中的分组信誉驱动机制

在P2P文件共享系统中,常会出现许多有策略的欺骗行为,而现有的信任模型并不能完全消除交易的风险。综合局部信任机制和全局信任机制,根据节点间相关的共享记录数据提出一种新的信誉计算方法,并进一步提出受信誉驱动的分组组织管理和节点搜索算法。仿真结果证明该信誉驱动机制能搜索到信誉值高的节点作为交易对象,并能有效降低系统面对合谋恶意节点和具有交易策略的恶意节点攻击时的交易风险。     

P2P网络中基于激励机制的信任模型

针对P2P网络提出一种信任模型。通过区分直接信任和间接信任,使推荐信任度主要依赖节点以往的成功推荐次数而非直接信任度,以抵御拥有较高直接信任度的节点对正常节点进行诋毁或欺骗。为避免非恶意节点因为网络延时等原因导致服务失败而被孤立出网络,引入激励机制和信任重建机制,定期提高非恶意节点的信任值,使其能重新加入网络,从而加强网络的容错性。实验结果表明,该模型能有效保护非恶意节点,孤立恶意节点,使网络具有更好的健壮性。     

基于信任向量的P2P信任机制

针对现有P2P信任机制不能有效地检测和惩罚短期内反复建立信任然后进行恶意攻击的摇摆节点,本文提出了基于信任向量和时间窗口的信任机制,用信任向量记录节点的交易信息,用时间窗口收集最近一段时间内交易的记录,提高了信任评估的准确性和动态性。仿真实验表明,与已有的信任机制相比,该机制能够有效处理动态恶意节点行为。     

P2P环境下引入激励机制的动态信任模型*

针对现有的P2P信任模型中对节点行为改变的动态适应能力不足以及欠缺激励机制的特点,提出了一种引入激励机制的动态信任模型（DITrust）。该模型采用信任值动态衰减策略以提高其动态适应能力,同时通过推荐偏移量来计算推荐信誉值,增加了推荐信誉的可信度;最后引入虚拟信誉货币以鼓励节点提供服务和推荐信息,提高了节点模型参与的主动性。实验结果表明,DITrust较已有的模型能够抵御类型更广泛的恶意节点攻击,且具有更小的网络开销。     

一种节点信誉相关的P2P网络信任管理模型

现有的P2P系统中存在大量的欺诈行为和不可靠的服务.本文通过模拟社会关系网络中信任的形成机制,提出P2P网络信任管理模型TMMRN,TMMRN通过考察节点的信誉值来进行安全交易,节点的信誉主要来自于其他节点对它的加权信任反馈,在信誉计算中增加了激励机制.TMMRN还可减少交易时的网络负担.实验表明TMMRN可提高信誉值的计算效率,能有效抵抗恶意节点的攻击,还可激励懒惰节点主动参与到系统中来.     

一种基于信任机制的混合式P2P模型

以改善P2P网络的安全性能为目标，介绍了基于关键节点的混合式P2P结构和基于信誉的信任机制，提出了一种基于该信任机制的混合式P2P模型，描述了该模型的工作机制。利用该模型可以在两个对等实体之间建立高效、可靠的信任关系，有效防止恶意攻击，提高P2P网络的效率和安全。     

TIM:一种P2P网络激励机制

在Peer-to-Peer网络中,Free-riding行为严重影响了P2P网络的可供使用的资源总量,降低了P2P网络的整体服务能力.针对这一问题,提出一种基于信任的激励机制TIM,适用于非结构化P2P网络.从多个方面统计了节点转发查询的能力,从而确定节点的查询被转发的范围;通过比较请求节点和服务节点的信誉来决定请求节点获取服务的概率;在选择响应节点时,优先选择信誉度高的服务节点.给出了信息的放置方法及查询转发、服务提供、响应处理三方面的算法.仿真实验和分析表明.激励机制TIM可以有效识别搭便车节点和恶意节点.并促进了节点之问的合作,提高了P2P网络的整体可用性.     

基于无限重复博弈的P2P网络信任模型研究

为解决P2P电子商务环境中存在的安全问题,针对现有一些信任模型的局限性,提出一种基于无限重复博弈理论的信任模型。通过建立奖惩策略,对节点的不合作行为,依据博弈策略对节点进行惩罚,同时对选择合作策略的节点进行奖励,并根据欺诈行为次数设定不同的惩罚周期。理论分析和仿真实验表明,合作策略会成为节点博弈的帕累托最优策略,该策略模型能有效遏制和惩罚恶意行为,提高节点诚实交易的积极性,从而有效提高网络环境的安全性和稳定性。     

P2P网络中双向信任机制的研究

P2P网络(Peer toPeer,对等网)已经以飞快的速度发展成为internet中最重要的应用系统之一。P2P网络开放、匿名的特性使得任何人在任何时候都也可加入网络为其他人提供内容和服务,同时也可以从网络中查找并获得所需要的资源。然而,也正是因为这种特点,节点之间缺乏信任、恶意节点随意终止服务,造成了网络的利用率低下,信任管理就显得十分必要。然而传统的单向信任管理机制难以有效地对自私节点和恶意节点进行控制。鉴于此,本文在研究P2P网络的信任管理机制的基础上,引入了双向信任机制,实现节点之间的双向评估。     

An incentive compatible reputation mechanism for P2P systems

In peer-to-peer (P2P) systems, peers often must interact with unknown or unfamiliar peers without the benefit of trusted third parties or authorities to mediate the interactions. Trust management through reputation mechanism to facilitate such interactions is recognized as an important element of P2P systems. It is, however, faced by the problems of how to stimulate reputation information sharing and honest recommendation elicitation. This paper presents an incentive compatible reputation mechanism for P2P systems. It has two unique features: (1) a recommender’s trustworthiness and level of confidence about the recommendation is considered for a more accurate calculation of reputations and fair evaluation of recommendations. (2) Incentive for participation and honest recommendation is implemented through a fair differential service mechanism. It relies on peer’s level of participation and on the recommendation credibility. Theoretic analysis and simulation show that the reputation mechanism we propose can help peers effectively detect dishonest recommendations in a variety of scenarios where more complex malicious strategies are introduced. Moreover, it can also stimulate peers to send sufficiently honest recommendations. The latter is realized by ensuring that active and honest recommenders, compared to inactive or dishonest ones, can elicit the most honest (helpful) recommendations and thus suffer the least number of wrong trust decisions.     

speedTrust: a super peer-guaranteed trust model in hybrid P2P networks

To curb malicious behavior, researchers have proposed a lot of trust models for P2P networks, most of which, however, suffer from the problems of high complexity, bad scalability and huge overhead due to the iterative trust calculations and the global search for feedbacks. In this paper, we propose a super peer-guaranteed trust model, speedTrust, for hybrid P2P networks. Considering the fact that the quality of services and feedbacks is the most important factor directly impacting on a trust model’s availability, we establish a feedback guarantee relationship between the service requester and its super peer, as well as a service guarantee relationship between the service provider and its super peer before a transaction begins. Moreover, a peer’s reputations are calculated using its pledged reputations for its involved transactions without any iterative operations. These features largely reduce the trust model’s complexity while discouraging peers from behaving maliciously for fear of being punished. The simulation results show that the speedTrust model is effective and efficient in terms of the successful transaction rate, the ability in curbing malicious behavior and the complexity.     

移动P2P网络基于博弈论方法的协作激励机制

在移动P2P网络中,部分自私的移动节点只是大量地消耗已有网络资源而不提供自己的资源。考虑到移动P2P网络的资源有限性以及部分节点具有自私行为的特点,提出了一种基于博弈论的协作激励机制。该机制根据移动节点的不同贡献大小来提供不同网络服务质量,最大限度地鼓励了每个移动节点参与协作和共享。同时,详细描述和分析了协作激励机制中的网络资源分配策略,并且证明了该协作激励机制的博弈存在一个稳定的纳什（Nash）均衡。通过仿真实验发现,该激励机制有效地激发了移动节点间的协作,优化了整个网络的性能。同现有的协作激励策略相比,提高了数据包转发率等。     

一种基于信誉的P2P的评价模型

随着P2P(Peer to Peer)技术的广泛使用,判断请求节点是否可信变得非常重要。介绍了一种基于信誉的P2P的评价模型,用于计算在P2P过程中各个节点之间所产生的信誉度,从而判断请求节点是否可信。这种模型综合考虑了自身以往经验以及其它节点对请求节点的意见。通过实验,发现此模型不仅可以阻止恶意节点对正常节点的攻击,还可以有效地提高正常节点对有组织攻击的抵抗能力。     

An Eigentrust dynamic evolutionary model in P2P file-sharing systems

Many reputation systems have been proposed to distinguish malicious peers and to ensure the quality of the service in P2P file sharing systems. Most of those reputation systems implicitly assumed that normal peers are always altruistic and provide their resources unconditionally when requested. However, as independent decision makers in real networks, peers can be completely altruistic (always cooperative, ALLC), purely selfish (always defective, ALLD), or reciprocal (R). In addition, those systems do not provide an effective method to reduce free-riders in P2P networks. To address these two problems, in this paper, we propose an EigenTrust evolutionary game model based on the renowned EigenTrust reputation model. In our model, we use evolutionary game theory to model strategic peers and their transaction behaviors, which is close to the realistic scenario. Many experiments have been designed and performed to study the evolution of strategies and the emergence of cooperation under our proposed EigenTrust evolutionary model. The simulation results showed that rational users are inclined to cooperate (enthusiastically provide resources to other peers) even under some conditions in which malicious peers try to destroy the system.     

一种基于概率统计方法的P2P系统信任评价模型

现有的P2P系统信任评价模型正面临着两种恶意节点的攻击行为--策略性欺骗和不诚实推荐,严重影响了模型计算节点信任评价的准确性和有效性.针对现有模型存在的不足,提出了一种基于概率统计方法的信任评价模型.该模型借鉴人类社会中主观信任关系的概念,依据直接经验和反馈信息,利用概率统计方法分别计算节点的直接信任和推荐信任,并通过区分直接经验的重要程度,区分反馈信息及其推荐者的可信度,提高信任评价模型的有效性.仿真实验分析说明,与已有的信任评价模型相比,该模型能够更有效地抑制策略性欺骗和不诚实推荐的威胁,特别是复杂的协同作弊方式对系统的攻击.     

On incentivizing upload capacity in P2P-VoD systems: Design,analysis and evaluation

Free riding has long been a serious problem in peer-to-peer (P2P) systems due to the selfish behavior of individual users. To conquer this problem, a key design issue of the P2P systems is to appropriately incentivize users to contribute resources. In P2P Video-on-Demand (VoD) applications, content providers need to incentivize the peers to dedicate bandwidth and upload data to one other so as to alleviate the upload workload of their content servers. In this paper, we design a simple yet practical incentive mechanism that rewards each peer based on its dedicated upload bandwidth. We use a mean field interaction model to characterize the distribution of number of peers in different video segments, based on which we characterize the content providers’ uploading cost as a function of the peers’ contribution. By using a game theoretic framework, we analyze the interaction between a content provider’s rewarding strategy and the peers’ contributing behaviors and derive a unique Stackelberg equilibrium. We further analyze the system efficiency in terms of the price of anarchy and study the long term behavior of the system under a repeated game setting. Via extensive simulations, we validate the stability and efficiency of our incentive scheme.     

A study on hybrid trust evaluation model for identifying malicious behavior in mobile P2P

P2P network has been widely used because of advantages such as efficient use of network bandwidth, saving of computing resources, and quick information exchange. In particular, the infra that manages each nodes centrally in P2P network does not exist and each node is a structure performing the sender and receiver roles. The service applying P2P technique in MANET is increased because this structure is very similar to the structure of MANET. However, the reliability may be lower by providing an erroneous service from malicious nodes because the supervision of management for nodes participating in P2P does not perform. In this paper, we propose hybrid trust evaluation technique based on Trust Zone structure to improve the reliability between nodes. TZM node is elected for trust evaluation of member nodes internal each TrustZone. The certificate of member nodes is issued in the elected TZM and the information is stored in TZMT. The data transmission of malicious nodes is blocked by limiting the data transmission of nodes that do not issued the certificate. The reputation-based trust management technique was applied to perform the fair file transmission of nodes and block the behavior of selfish nodes. The excellent performance of the proposed technique in this paper was confirmed through experiments.     

Trust-based exchange of services to motivate cooperation in P2P networks

In this paper we propose a trust-based exchange framework to motivate cooperation among peers of different consumption, contribution and service evaluation profiles. Our framework consists of distributed resource allocation and server selection policies based on local reputation vectors. We present how proposed policies outperform previous work and lead to the autonomic formation of coalitions between peers who mutually profit by exchanging their services. In this way the utilities of all peers progressively improve without pre-existing knowledge of one another’s service evaluation and capability profiles. Peers’ coalitions are dynamically reformatted, adapting to network changes, e.g., when new peers enter the system or peers vary their profiles. Only misbehaving (non contributive) peers cannot benefit by our framework, which efficiently blocks misbehavior.