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.     

Multifactor hierarchical fuzzy trust evaluation on peer-to-peer networks

Decentralized Peer-to-Peer (P2P) networks offer not only opportunities but also threats. Due to the autonomy, self-interest and heterogeneousness of peers, the interaction outcomes are uncertain. One way to minimize the threats in such an open environment is exploiting the reputation method to evaluate the trustworthiness and predict the future behaviors of peers. While most of the existing reputation-based trust models focus on preventing network from the malicious peers, peers’ capabilities to fulfill the tasks are mostly ignored. In this paper, we present a novel trust model MHFTrust which quantifies and compares the trustworthiness of peers based on hierarchical fuzzy system. Six capability factors are identified to describe the peers’ trust on the capability, and one security factor, named “Malicious behavior” is used to evaluate the peers’ trust on security. Our trust model consisted of local-trust computation based on fuzzy techniques and global reputation aggregation, which integrates feedback from other peers to produce a global reputation for each peer. Credibility and weight of feedback are introduced to facilitate the computation of global reputation. It is shown in simulation that our trust model greatly improves the efficiency of P2P system, while the number of inauthentic files on the network is significantly decreased.     

一种新的P2P安全信任管理模型

由于P2P网络的特性,传统的信任机制难以对其应用中存在的冒名,诋毁等安全问题,进行合理的解决。在现有信任模型的基础上提出了一个新的P2P安全信任管理模型,该模型负责节点信任度的评估、更新,信任度的评估方法不仅考虑了节点自身的交易历史,同时也考虑了其他节点的推荐,并且每次交易后,都要根据本次交易的情况,及时修改节点之间的个人交互度和推荐节点的推荐可信度,使信任度能正确地反映节点的信誉,能够有效地预防冒名、诋毁等现象。     

Behavior-based reputation management in P2P file-sharing networks

Trust research has become a key issue in the last few years as a novel and valid solution to ensure the security and application in peer-to-peer (P2P) file-sharing networks. The accurate measure of trust and reputation is a hard problem, most of the existing trust mechanisms adopt the historical behavior feedback to compute trust and reputation. Thus exploring the appropriate transaction behavior becomes a fundamental challenge. In P2P system, each peer plays two roles: server and client with responsibility for providing resource service and trust recommending respectively. Considering the resource service behavior and trust recommending behavior of each peer, in this paper, we propose a new trust model adopting the technology to calculate eigenvectors of trust rating and recommending matrices. In our model, we define recommended reputation value to evaluate the resource service behavior, and recommending reputation value to evaluate the trust recommendation behavior. Our algorithm would make these two reputation values established an interrelated relation of reinforcing mutually. The normal peers provide authentic file uploading services, as well as give correct trust recommendation, so they can form a trusted and cooperative transaction community via the mutual reinforcement of recommended and recommending reputation values. In this way, the transaction behaviors of those malicious peers are isolated and confined effectively. Extensive experimental results also confirm the efficiency of our trust model against the threats of exaggeration, collusion, disguise, sybil and single-behavior.     

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。     

一种基于差评散布的P2P网络信任机制

面对各种网络攻击,P2P网络需要有效的信任机制隔离恶意节点,保证节点的成功交易。考虑节点行为特征和差评的重要性,提出基于差评散布的信任机制。服务节点一旦提供的服务被给出差评,对其近期交易的相关节点进行差评的散布,加大差评对服务节点声誉的影响力度。经过二次计算的节点声誉值能真实反映节点近期的声誉水平与交易趋势。实验结果表明,该信任机制能保证正常节点的交易成功率,有效对抗各种攻击行为。     

P2P声誉系统中GoodRep攻击及其防御机制

声誉系统由于其聚集评价的特点,为恶意节点提供了可乘之机.一些恶意节点合谋形成GoodRep攻击组,相互虚假夸大,进而在高声誉值的掩饰下危及P2P网络安全.提出了GoodRep的攻击模型及其防御机制——RatingGuard,并给出了该机制的数学描述和模块化实现过程.RatingGuard通过分析推荐节点之间的评价行为相似度,对推荐节点进行聚类划分和异常检测,识别出存在的GoodRep攻击组节点,从而帮助声誉系统排除GoodRep攻击组的干扰.仿真结果表明,RatingGuard在GoodRep攻击组的抵制方面效果显著,有效提高了声誉系统在面对GoodRep攻击时的恶意节点检测率.     

A GroupTrust model based on service similarity evaluation in P2P networks

The open and anonymous nature of peer‐to‐peer (P2P) networks makes it an ideal medium for attackers to spread malicious contents, which in turn leads to lower quality of network services due to lack of effective trust management mechanism. To improve the quality of services (or transactions), this paper proposes a novel trust and reputation model, named as GroupTrust, based on peer group and evaluation similarity degree in P2P networks. In the proposed model, trust relationships between peers are divided into three categories: trust relationship within a peer group, trust relationship between different groups, and trust relationship between a peer in a peer group with another peer out of this peer group. The model presents the evaluation similarity degree under different context of services and gives local and global reputation computation. Experimental results demonstrate that this model can get more real trust value and deal with the malicious attacks efficiently by comparison with existing models. © 2010 Wiley Periodicals, Inc.     

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.     

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.     

一种考虑节点角色的P2P信任模型

在对等网络中,如何对节点行为进行准确的评估是信任模型研究的重点.经过学习和分析,发现现有的模型几乎都是基于节点作为被推荐者这一角色,而忽略了自身的推荐角色.对此本文提出两重推荐信任模型,从节点的两重角色考虑,为每个节点设计两重评估标准.若干次交易后,该模型能够使正常节点形成紧密的交易关系,有效地遏制了恶意节点的交易行为.实验表明该模型在面对夸大、合谋、伪装和单一行为威胁时较其他一些模型更具有效性.     

Characterizing Economic and Social Properties of Trust and Reputation Systems in P2P Environment

Considering the fact that P2P （Peer-to-Peer） systems are self-organized and autonomous, social-control mechanism （like trust and reputation） is essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest and malicious peer behaviors. So, naturally, we advocate that P2P systems that gradually act as an important information infrastructure should be multi-disciplinary research topic, and reflect certain features of our society. So, from economic and social perspective, this paper designs the incentive-compatible reputation feedback scheme based on well-known economic model, and characterizes the social features of trust network in terms of efficiency and cost. Specifically, our framework has two distinctive purposes： first, from high-level perspective, we argue trust system is a special kind of social network, and an accurate characterization of the structural properties of the network can be of fundamental importance to understand the dynamics of the system. Thus, inspired by the concept of weighted small-world, this paper proposes new measurements to characterize the social properties of trust system, that is, high global and local efficiency, and low cost; then, from relative low-level perspective, we argue that reputation feedback is a special kind of information, and it is not free. So, based on economic model, VCG （Vickrey-Clarke-Grove）-like reputation remuneration mechanism is proposed to stimulate rational peers not only to provide reputation feedback, but truthfully offer feedback. Furthermore, considering that trust and reputation is subjective, we classify the trust into functional trust and referral trust, and extend the referral trust to include two factors： similarity and truthfulness, which can efficiently reduce the trust inference error. The preliminary simulation results show the benefits of our proposal and the emergence of certain social properties in trust network.     

一种基于共享时长的P2P用户评价机制

在P2P文件共享网络现有声誉系统中,评价信息不足和恶意评价导致声誉不可靠。为此,提出一种基于下载节点共享时长的客观评价方法。该方法使系统自动获得每个下载节点的评级信息,根据该信息建立节点之间的信任关系。仿真结果表明,共享时长方法可提高信任的可靠性,有效隔离恶意节点,并能为不同行为的节点提供分化服务,保证网络资源分配的公平性。     

采用排名反馈的P2P名誉评价模型

P2P网络中的节点很可能从另外的节点那里收到质量很差的服务和信息,名誉评价是解决该问题的常见方法.基于评分反馈的P2P名誉计算机制存在下述缺点:无法区分恶意评价和诚实节点给出错误评价间的差别;需要对评分可信度进行二次评价,使名誉计算速度减慢;用数字来表示节点名誉的方式不够自然.实际上,名誉评价的用途是确定节点可信度的相...     

一个非结构化P2P网络中基于信誉的激励机制

在P2P网络中,freerider节点和恶意节点的不合作行为严重影响了P2P服务的可用性。为此,本文提出了一个应用于非结构化P2P环境下基于信誉的激励机制。该机制通过有限的信任信息的共享,实现信任评估和推荐信任度评估;并以此为基础,通过有效的拓扑构造和服务选择策略及服务请求冲突解析策略的选择,实现对合作节点的激励和对freerider和恶意节点的遏制及惩罚。分析及仿真实验表明,本文提出的基于信誉的激励机制是简单有效的。     

Reputation management algorithms for DHT-based peer-to-peer environment

This paper addresses the problem of integration of reputation management mechanisms into data look-up and routing processes to cope with some specific security problems in peer-to-peer (P2P) networks based on Distributed Hash Tables (DHT). The goal is to find a mode for “good” peers to cooperate in order to withstand malicious activity of single malevolent peers and their collusions as well.We start from consideration of individual instruments for reputation evaluation that every single peer should be provided with to autonomously define the level of its own trust towards others. We also propose a possible scenario of integration of some existing reputation management techniques and routing mechanisms in a P2P network based on the popular Kademlia algorithm. Then, we present an interaction algorithm that allows peers to obtain the global trust value for each single node through exchanging opinions in the form of local trust values independently calculated by every peer with other members of the community. Such collaboration between peers is indispensable to cope with malicious activity of inconsistent nature specific to DHT-based environment. To render the algorithm resilient to the presence of malicious participants we propose to apply solutions for Byzantine Agreement to exchange opinions among peers. We also provide mathematical evaluations concerning the complexity and computational costs of the proposed algorithm that evidence apparent improvements over the previous one.     

一种基于反馈可信度的分布式P2P信任模型

开放、共享与匿名的Peer-to-Peer(简称P2P)网络已经取得了越来越多的应用,无中心对等的特性也吸引了越来越多的用户.但由于其网络中的节点不受约束,资源的共享是用户自愿的行为,因此节点间的信任很难通过传统的信任机制建立.一种可行的解决方案是借鉴人际网络中的信任关系,建立一种基于信誉的全局信任模型.已有的工作基本建立在信任度高的节点其反馈也更可信这个假设的基础上,将节点的反馈质量简单地等同于服务质量.针对这一问题,提出了一种基于节点反馈可信度的分布式P2P全局信任模型(简称FCTrust),用于量化和评估节点的可信程度,并给出了模型的数学表述和分布式实现方法.分析及仿真实验结果表明,FCTrust较已有的全局信任模型在遏制更广泛类型的恶意节点攻击的有效性、迭代计算的收敛性及消息成本上有较大提高.     

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。     

SyMon: A practical approach to defend large structured P2P systems against Sybil Attack

Sybil attack is one of the most challenging problems that plague current decentralized Peer-to-Peer(P2P) systems. In Sybil attack, a single malicious user creates multiple peer identities known as sybils. These sybils are employed to target honest peers and hence subvert the system. In this paper, we describe a novel solution that enables all honest peers to protect themselves from sybils with high probability in large structured P2P systems. In our proposed sybil defense system, we associate every peer with another non-sybil peer known as SyMon. A given peer’s SyMon is chosen dynamically such that the chances of both of them being sybils are very low. The chosen SyMon is entrusted with the responsibility of moderating the transactions involving the given peer and hence makes it almost impossible for sybils to compromise the system. We show the effectiveness of our proposed system in defending against Sybil attack both analytically and experimentally. In addition to this, we explore the feasibility of our proposed solution in two P2P applications: reputation systems for P2P based file sharing applications and P2P applications susceptible to Denial-of-Service(DOS) attack, systems known to be highly vulnerable to Sybil attack. In each of our case studies, we discuss possible ways in which our solution can be employed to defend the system against Sybil attack.     

一种激励相容的P2P信誉模型

针对现有的信任模型不能很好地处理P2P网络环境中恶意节点提供虚假服务的欺作行为,及不积极提供诚实推荐的问题,提出了一种激励相容的P2P信誉模型(简称ICRM)。该模型使用时间区间的概念来标示经验和推荐的时间特性,利用直接信任度、推荐信任度及推荐可信度等机制来精确描述节点的实际信任等级,并引入参与层次来度量节点提供推荐的积极程度,从而有效地识别与抑制不同类型的恶意节点,激励节点积极提供诚实推荐。仿真实验表明,ICRM能够有效地抑制恶意节点的欺作行为及不诚实反馈行为,并能有效解决节点推荐积极性不高的问题。