P2P系统信任模型研究

由于P2P系统的开放、匿名等特征,使其成为一些恶意节点发布虚假信息的温床。因此,在P2P环境中建立一个完善的信任机制显得尤为重要。本文提出了一种新的基于确定性理论的P2P系统信任模型,系统根据该模型计算出每个相关节点的信任度,节点依据计算结果与信任度高的节点进行交易。分析及仿真表明,该模型能有效地隔离恶意节点,防止恶意信息的散播。     

P2P网络中恶意节点控制算法的研究

对目前P2P网络中的信任模型进行研究,发现信任模型在考虑恶意节点方面存在欠缺。为此,分析恶意节点的恶意行为,综合已有模型的优点,根据信任值的“慢升快降”与直接信任度影响更大的原则,针对控制恶意节点提出一种新的信任度计算模型,该模型中信任度的改变值与每次交易的资源大小有关。仿真实验结果证明,该模型能提升交易成功率。     

P2P系统中基于声誉的信任评估机制

P2P系统能够使陌生节点之间进行在线交易,但安全问题越来越受到人们的关注。因此,如何在P2P系统中构建一个有效的信任机制来帮助在节点之间建立信任是目前P2P技术研究的一个热点。提出了一种新的P2P系统中基于声誉的信任评估机制,该机制较全面地考虑了影响信任度的因素,改进了局部声誉与全局声誉的计算方法,降低了信任度的计算负载,并且引入了黑名单机制。实验结果表明,该机制能有效地评估节点的信任度,识别和隔离恶意节点,提高系统交易成功率,并能有效地应用于P2P系统中。     

一种基于群组的P2P网络信任管理模型*

针对 P2P 网络中存在的多种恶意行为,提出一种基于群组的信任管理模型。该模型采用分组策略,引入直接信任度、组内信任度、组间信任度及多种控制因子来计算节点总体信任度,提高了信任机制的可靠性。仿真实验表明,该模型能够有效抑制多种恶意行为,提高系统成功交易率,使节点之间更有效地建立信任关系。     

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。     

一种P2P电子商务系统中基于声誉的信任机制

P2P电子商务系统中恶意节点的存在会破坏系统的正确性和可用性.基于声誉的信任机制通过计算节点的信任度可以识别出恶意节点.这种机制的可用性依赖于信任度的计算方法、信任机制的准确性及其抗攻击能力.然而,P2P环境下已有的信任机制在上述3个方面都存在着一些问题.这些问题的解决取决于影响信任度的信任因素的选取.因此,提出了一种新的P2P电子商务系统中基于声誉的信任机制.在该机制中,一个节点具有两种类型的声誉.一个节点相对于另一个节点的局部声誉是根据另一个节点对其交易行为的评价来计算的.一个节点的全局声誉是根据所有与其交易过的节点对它的评价来计算的.通过较全面地引入影响信任度的信任因素,既解决了局部声誉和全局声誉的精确计算问题,又提高了信任机制抗攻击的能力.为了确定节点所给评价的真实性,提出了一个节点评价的质量模型,并给出了节点评价的可信度计算方法.在计算信任度的过程中,利用置信因子来综合局部声誉和全局声誉,并给出置信因子的确定方法.最后,对信任机制的有效性和抗攻击能力进行了理论分析和实验验证.结果表明,提出的信任机制优于其他现有的方法,能够有效地应用于P2P电子商务系统中.     

P2P网络环境下基于推荐的信任模型

基于网络中节点之间不仅仅局限于直接交易建立起来的信任关系,还包括了第三方推荐信任的事实,提出了在P2P网络环境下基于推荐的信任模型。该模型用成功次数与失败次数在总交易数目中的比例作为直接信任度,将交易信誉与推荐信誉明确区分出来,引入了偏移因子计算推荐节点的可信性,通过惩罚因子和风险因素动态平衡节点直接信任度和其他节点的推荐信任度,得到目标节点的综合信任值,并给出仿真实验验证。实验结果证明,模型计算的综合信任值更趋近其真实值,并且能抵抗恶意节点的诋毁、协同作弊等威胁。     

P2P电子商务信任模型研究

为解决P2P电子商务中恶意节点的欺诈问题,提出一种电子商务信任模型。模型采用带超级节点的混合P2P网络拓扑结构,将P2P网络划分为不同的域,对域内和域间节点分别进行信任度的计算。模型考虑到交易金额和时间等因素,提高了对信任度计算的准确性。实验结果表明,模型可有效减少恶意交易行为的发生。     

GBTM：一种P2P系统中基于群组的信任模型

目前在P2P网络中,缺乏有效的机制来提高系统的安全性,存在许多恶意行为,信任模型已经成为P2P应用研究的一个重要课题。文中对基于信任机制的P2P网络进行研究,根据节点的兴趣、爱好建立不同群组,节点总体信任度由节点之间直接信任度、组与节点之间信任度、组间信任度以及多重参数合成,并通过针对诋毁恶意节点攻击、协同作弊攻击两种不同的攻击模式下的仿真实验表明,该模型具有较高的下载成功,并且能使节点负载处于可控范围内。     

一种基于文件附加信息的P2P信任模型

在P2P文件共享系统中,存在不少节点不主动提供资源甚至提供虚假、恶意的资源.为了孤立这些恶意节点和鼓励节点多共享自己的文件,在分析一些现有信任模型的基础上,提出了基于文件附加信息的信任模型,该模型从文件的信任度出发导出用户的信任度,并在计算过程中考虑了相关因素,激励用户多为整个P2P网络做贡献,从而提高了整个网络的活力.通过实验仿真和分析表明:该模型能有效地隔离恶意节点,提高交易成功率,可使节点之间更有效地建立互信关系,进而提高系统的稳定性和可靠性.     

一种基于主观逻辑理论的P2P网络信任模型

由于P2P系统的开放、匿名等特点，使得P2P系统对节点缺乏约束机制，节点间缺乏信任。针对以上问题本文提出了一种基于主观逻辑理论的P2P网络信任模型，并在信任的计算中引入风险的机制，有效防止协同作弊和诋毁的安全隐患。实验和分析结果表明，这种信任模型能更加精确地评估节点的信任度，从而能更加有效地解决P2P网络环境中存在的安全问题。     

一种基于组群的P2P网络信任模型*

由于P2P网络的开放、匿名等特点,使得P2P网络对节点缺乏约束机制,节点间缺乏信任。提出了一种应用于非结构化P2P网络的信任模型——BGTrust。该模型对组群内信任采用局部推荐信任和组群间信任采取全局信任的方法进行处理,充分结合了全局信任和局部信任的优点。仿真表明,该信任模型在对交互的信任度评价可信度和抑制恶意节点方面较已有模型有一定改进。     

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.     

BitTorrent中一种基于全局贡献的节点选择策略

BitTorrent采用基于速率的Tit-For-Tat（Rate-based TFT）阻塞算法和乐观激活（Optimistic Unchoke,OU）算法为节点选择策略：上传节点采用Rate-based TFT算法选择为自身提供文件块上传速度最快的4个请求节点为下载节点,采用OU算法随机选择其他1个请求节点为下载节点。BitTorrent中Rate-based TFT算法只考虑邻居为上传节点所上传的文件块数即直接贡献,资源利用率不高,不能有效保证上传/下载之间的公平性。提出一种基于全局贡献的节点选择策略（Contribution-based TFT）,从直接贡献和间接贡献（即对其他节点所上传的文件块）两方面来考虑某段时间内节点的全局贡献,贡献越多,获取下载服务的优先权限越高。模拟实验表明,基于全局贡献的节点选择策略提高了上传配额利用率,减少了文件下载时间,并保证了公平性。     

Stochastic Optimization for Content Sharing in P2P Systems

Available resources in peer-to-peer (P2P) systems depend strongly on resource contributions made by individual peers. Empirical data shows that in the absence of incentives, a majority of the participating peers do not contribute resources. Modeling interactions between individual peers is often difficult as the number of peers in the system can be very large, and the relationships among them can be very complex. In this paper, we propose a new solution for P2P systems, where peers upload and download content to and from the contributing peers based on agreed-upon/determined sharing rates. We propose a P2P solution that deters free-riders by imposing constraints on participating peers; specifically, a peer is allowed access to new content only as long as its own content contribution exceeds an adaptively set threshold. The constraints are enforced either by a central authority (e.g., a tracker) or by a decentralized coalition of peers in a swarm, social network, etc. We derive optimal upload policies for the peers given their estimated future download requirements and their previous contribution (credit) to the other peers. Our results show considerable improvement in the cost-benefit tradeoff for peers that deploy such an optimal policy as compared to heuristic upload policies. We also propose mechanisms based on which the coalition of peers can provide incentives or penalties to participating peers to adjust their policies such that the availability of content and/or number of peers contributing content is maximized.     

On the expected file download time of the random time-based switching algorithm in P2P networks

The expected file download time of the random time-based switching algorithm for peer selection and file downloading in a peer-to-peer (P2P) network is still unknown. The main contribution of this paper is to analyze the expected file download time of the time-based switching algorithm for file sharing in P2P networks when the service capacity of a source peer is totally correlated over time, namely, the service capacities of a source peer in different time slots are a fixed value. A recurrence relation is developed to characterize the expected file download time of the time-based switching algorithm. It is proved that for two or more heterogeneous source peers and sufficiently large file size, the expected file download time of the time-based switching algorithm is less than and can be arbitrarily less than the expected download time of the chunk-based switching algorithm and the expected download time of the permanent connection algorithm. It is shown that the expected file download time of the time-based switching algorithm is in the range of the file size divided by the harmonic mean of service capacities and the file size divided by the arithmetic mean of service capacities. Numerical examples and data are presented to demonstrate our analytical results.     

构造基于推荐的Peer-to-Peer环境下的Trust模型

在诸如文件共享等无中心的Peer-to-Peer环境中,资源共享是用户自愿的行为.在这类系统中,由于用户不为自身的行为担负(法律)责任,因而节点间的信任关系往往很难通过传统的信任机制建立.一种更合理的考虑是参考人际网络中基于推荐的信任关系建立方法.现有的模型不能很好地解决模型的迭代收敛性问题,同时缺乏对诸如冒名、诋毁等安全性问题的考虑.针对上述问题,在节点推荐的基础上提出了一种基于Peer-to-Peer环境的信任模型,并给出了该模型的数学分析和分布式实现方法.分析及仿真表明,该信任模型较已有模型在迭代的收敛性、模型的安全性等问题上有较大改进.     

Analysis of file download time in peer-to-peer networks with stochastic and time-varying service capacities

The service capacities of a source peer at different times in a peer-to-peer (P2P) network exhibit temporal correlation. Unfortunately, there is no analytical result which clearly characterizes the expected download time from a source peer with stochastic and time-varying service capacity. The main contribution of this paper is to analyze the expected file download time in P2P networks with stochastic and time-varying service capacities. The service capacity of a source peer is treated as a stochastic process. Analytical results which characterize the expected download time from a source peer with stochastic and time-varying service capacity are derived for the autoregressive model of order 1. Simulation results are presented to validate our analytical results. Numerical data are given to show the impact of the degree of correlation and the strength of noise on the expected file download time. For any chunk allocation method, an analytical result of the expected parallel download time from a source peer with stochastic and time-varying service capacity is derived. It is shown that the algorithm which chooses chunk sizes proportional to the expected service capacities has better performance than the algorithm which chooses equal chunk sizes. It is also shown that multiple source peers do reduce the parallel download time significantly.     

基于网络编码的P2P流媒体

本文提出了一种基于网络编码的P2P流媒体直播方案。在该方案下，Peer节点对流经它的数据先进行网络编码，再进行转发，以提高Peer节点实际的下载速率以及对网络资源的利用率。仿真实验表明，采用网络编码后节点的播放质量得到了普遍性的增强。     

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system,in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers.Such queries are based on local filter query statistics,and require as less communication cost as possible,which makes it more difficult than the existing distributed k-NN queries.Especially,we hope to reduce candidate peers and degrade communication cost.In this paper,we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries.Our approach is especially suitable for continuous k-NN queries when updating peers,including changing ranges of peers,dynamically leaving or joining peers,and updating data in a peer. In addition,simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR.)-based query approaches,especially for continuous queries.