基于兴趣和信任评价的P2P语义社区模型

针对大规模网络中P2P信息共享面临的资源定位问题和“搭便车”现象,在考虑节点语义相似度、信任度和活跃强度的基础上,提出一种语义社区构建方法,提高P2P资源组织的结构性和定位准确性。建立基于信任评价的语义社区动态调整机制,以减少或消除“搭便车”的节点。     

VectorTrust: trust vector aggregation scheme for trust management in peer-to-peer networks

With emerging Internet-scale open content and resource sharing, social networks, and complex cyber-physical systems, trust issues become prominent. Conventional trust mechanisms are inadequate at addressing trust issues in decentralized open environments. In this paper, we propose a trust vector based trust management scheme called VectorTrust for aggregation of distributed trust scores. Leveraging a Bellman–Ford based algorithm for fast and lightweight trust score aggregation, VectorTrust features localized and distributed concurrent communication. Built on a trust overlay network in a peer-to-peer network, a VectorTrust-enabled system is decentralized by nature and does not rely on any centralized server or centralized trust aggregation. We design, implement, and analyze trust rating, trust aggregation, and trust management strategies. To evaluate the performance, we design and implement a VectorTrust simulator (VTSim) in an unstructured P2P network. The analysis and simulation results demonstrate the efficiency, accuracy, scalability, and robustness of VectorTrust scheme. On average, VectorTrust converges faster and involves less complexity than most existing trust schemes. VectorTrust remains robust and tolerant to malicious peers and malicious behaviors. With dynamic growth of P2P network scales and topology complexities, VectorTrust scales well with reasonable overheads (about O(lg?N) communication overheads) and fast convergence speed (about O(log? _D N) iterations).     

Trustworthy-based efficient data broadcast model for P2P interaction in resource-constrained wireless environments

In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer?s reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer?s credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.     

METrust: A mutual evaluation-based trust model for P2P networks

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer (P2P) network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.     

P2P中一种改进的可信模型

对基于贝叶斯网络的可信模型中的资源搜索算法和可信度计算方法进行重新设计,本文提出一种改进的P2P可信模型。改进后的资源搜索算法使节点接收到的冗余包数量减少 ,并提高了系统的可靠性。在此基础上,针对P2P网络的匿名性,提出了一种新的运用服务次数和对评价值取对数方式进行可信度计算和更新的方法。此方法可以有效地阻止 恶意节点对正常节点和可信节点的攻击,同时还可防止恶意节点间通过小集团合作方式来提高各自节点的可信度。实验结果表明,本模型较现有模型在抑制P2P网络中恶意节点的活动方面具有更好的效果,且增加了系统服务可靠性．     

基于Super-node结构的P2P网络的信誉评价系统

针对基于Super-node结构的P2P网络提出了一个新的简单的信誉评价系统。该系统除了能根据其它对等点的反馈信息来建立对等点之间的信任关系外,还能帮助识别一些恶意对等点,从而保证整个P2P网络的正常运行。     

一种基于普遍信任的P2P资源选择方法

网络中的资源评价者分为个体和团体两类。以不同评价者的信任评价为基础,提出了一种P2P网络资源选择方法。给出个体和团体对资源的片面信任计算方法,得到资源的普遍信任度的综合计算方法。提出为用户确定可取信评价者的范围,实现以可取信者为转发对象的资源查询转发。从候选资源中选择出普遍信任度最高的资源。     

An adaptive overlay network inspired by social behaviour

Nature is a great source of inspiration for scientists, because natural systems seem to be able to find the best way to solve a given problem by using simple and robust mechanisms. Studying complex natural systems, scientists usually find that simple local dynamics lead to sophisticated macroscopic structures and behaviour. It seems that some kind of local interaction rules naturally allow the system to auto-organize itself as an efficient and robust structure, which can easily solve different tasks. Examples of such complex systems are social networks, where a small set of basic interaction rules leads to a relatively robust and efficient communication structure. In this paper, we present PROSA, a semantic peer-to-peer (P2P) overlay network inspired by social dynamics. The way queries are forwarded and links among peers are established in PROSA resemble the way people ask other people for collaboration, help or information. Behaving as a social network of peers, PROSA naturally evolves to a small world, where all peers can be reached in a fast and efficient way. The underlying algorithm used for query forwarding, based only on local choices, is both reliable and effective: peers sharing similar resources are eventually connected with each other, allowing queries to be successfully answered in a really small amount of time. The resulting emergent structure can guarantee fast responses and good query recall.     

基于信任的对等网络拓扑构造

在对等网络中．通常使用信任和声望机制来建立节点间的信任关系，以指导用户选择可信的协作节点．本文给出了一个基于信任的对等网络拓扑构造机制，使节点可以通过交互经验和其他节点的反馈采建立对目标节点的信任，并相应地更新同目标节点的链接关系，以便利之后的交互，并提高整个网络的交互性能．仿真实验测试了本文给出的方案．并证明了其效率．     

一种时域上的P2P信任模型

传统的P2P信任是根据节点间交易成功和失败的次数来合成的,该值是个累积量,而实际的信任值是时变量。提出了一种新的P2P时域信任模型,对于局部信任,通过对每个时间段合成一个信任,然后根据时间段的新近赋予不同的加权合成局部信任;对于全局信任来说,随着时间的推移,发起节点会越来越重视自身对目标节点的信任评价,而其它节点的推荐值会得以削弱。该模型刻画了信任的动态性,能够有效地防止不良节点的信任短期积聚以及依靠其它节点共谋等恶意行为。     

Self-nominating trust model based on hierarchical fuzzy systems for peer-to-peer networks

Security is a critical constraint for the expansion of Peer-to-Peer (P2P) networks. The autonomy, dynamic and distribution natures benefit both valid and malicious users and also lead that P2P networks are extremely susceptible to malicious users. Exploiting a reputation-based trust model is a feasible solution in such an open environment to build trust relationship among peers. While most of existing trust models focus on restraining the abuse and malicious attacks, intentions and sharing capabilities of peers are mostly ignored. In this paper, we present a self-nominating trust model based on hierarchical fuzzy systems to quantify the behaviors of peers. The reputation is defined based on eight factors, where three promising factors are provided by resource holders to demonstrate their desires, and four capability factors are recorded by requesters to identify the provider’s service capability. The approach degree based updating recommendation is deployed to aggregate the global trust metrics. Experimental results illustrate that our trust model effectively improves the efficiency and security of P2P systems.     

P2P网络的信任评估安全模型研究

5C中针对当前P2P网络安全的需要,提出了一种信任评估网络安全模型,给出了新的信任评估计算方法和仿真实验。文中提出的信任评估模型是属于对等信任模型,该模型适合P2P网络的分布式结构,也适应于P2P网络对节点保持对等、独立、自由和异构的要求。实验结果表明,在P2P网络中建立起对等的信任评估模型,其效果是明显的。P2P网络中的节点能通过模型算法来判断来访节点的情况,通过对来访者真实情况的甄别和判断,能拒绝恶意节点的入侵,有效地抑制了网络中恶意节点的攻击成功次数。     

Emergent Semantics and Cooperation in Multi-knowledge Communities: the ESTEEM Approach

In the present global society, information has to be exchangeable in open and dynamic environments, where interacting users do not necessarily share a common understanding of the world at hand. This is particularly true in P2P scenarios, where millions of autonomous users (peers) need to cooperate by sharing their resources (such as data and services). We propose the Esteem approach (Emergent Semantics and cooperaTion in multi-knowledgE EnvironMents), where a comprehensive framework and a platform for data and service discovery in P2P systems are proposed, with advanced solutions for trust and quality-based data management, P2P infrastructure definition, query processing and dynamic service discovery in a context-aware scenario. In Esteem, semantic communities are built around declared interests in the form of manifesto ontologies and their autonomous nature is preserved by allowing a shared semantics to naturally emerge from the peer interactions. Inside the borders of semantic communities data and services are discovered, queried and invoked in a resource sharing scenario, where the context in which users interoperate and the trust of exchanged information are also relevant aspects to take into account.     

The ESTEEM platform: enabling P2P semantic collaboration through emerging collective knowledge

In this paper, we present Esteem (Emergent Semantics and cooperaTion in multi-knowledgE EnvironMents), a community-based P2P platform for supporting semantic collaboration among a set of independent peers, without prior reciprocal knowledge and no predefined relationships. Goal of Esteem is to go beyond the existing state-of-the-art solutions for P2P knowledge sharing and to provide an integrated platform for both data and service discovery. A distinguishing feature of Esteem is the use of semantic communities to explicitly give shape to the collective knowledge and expertise of peer groups with similar interests. Key techniques of Esteem will be presented in the paper and concern: shuffling-based communication, ontology and service matchmaking, context management, and quality-aware data integration. An application example of data and service discovery in the health-care domain will be presented, by also discussing results of system and user evaluation.     

基于资源评价的信任管理模型

针对P2P网络中交易的安全性问题,提出了一种基于资源评价的信任管理模型。首先给出评价节点行为信任的好评度的概念,用模糊综合评判的方法计算节点对交易的单次好评度,每次交易后的交易记录表由提供资源的节点的母节点进行管理和存储;当节点选择提供资源的节点时,不仅考虑对目标节点的直接信任度,还考虑此次交易资源的总好评度,在计算直接信任度时考虑了时效性和交易资源的重要程度两个因素,交易资源的总好评度的计算数据来源于该资源的评价节点给出的以往评价;最后引入了基于虚拟货币的激励机制,以有效地提高节点参与的积极性。仿真实验表明,该模型能有效抵制恶意节点的攻击,提高网络交易的成功率。     

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。     

H-Trust: A Group Trust Management System for Peer-to-Peer Desktop Grid

Peer-to-Peer Desktop Grid (P2PDG) has emerged as a pervasive cyber-infrastructure tackling many large-scale applications with high impacts. As a burgeoning research area, P2PDG can support numerous applications, including scientific computing, file sharing, web services, and virtual organization for collaborative activities and projects. To handle trustworthiness issues of these services, trust and reputation schemes are proposed to establish trust among peers in P2PDG. In this paper, we propose a robust group trust management system, called H-Trust, inspired by the H-index aggregation technique. Leveraging the robustness of the H-index algorithm under incomplete and uncertain circumstances, H-Trust offers a robust personalized reputation evaluation mechanism for both individual and group trusts with minimal communication and computation overheads. We present the H-Trust scheme in five phases, including trust recording, local trust evaluation, trust query phase, spatial-temporal update phase, and group reputation evaluation phases. The rationale for its design, the analysis of the algorithm are further investigated. To validate the performance of H-Trust scheme, we designed the H-Trust simulator HTrust-Sim to conduct multi-agent-based simulations. Simulation results demonstrate that H-Trust is robust and can identify and isolate malicious peers in large scale systems even when a large portion of peers are malicious.     

对抗共谋及节点行为动态性的P2P信任模型

针对现有P2P信任模型存在的网络开销大、不能很好地处理节点行为的动态性改变及共谋攻击等问题,提出了一种新的信任模型。通过直接交互节点的局部评价加权其评价可信度计算节点的全局信誉值;采用基于局部评价标准差、局部评价集中度的方法识别和抑制共谋攻击;根据节点行为的改变动态更新其信誉值和评价可信度。仿真实验表明,提出的模型较现有模型在网络开销、抑制共谋攻击和节点行为的动态性等方面有较大改进。     

网格经济模型中的一种可信调度算法

在Buyya设计的GRACE网格资源管理框架下提出一种改进的可信模型.针对网格的动态性,提出一种新的运用服务次数和对评价值取对数方式进行可信度计算和更新的方法.此方法可以有效地阻止恶意节点对正常节点和可信节点的攻击,同时还可防止恶意节点间通过小集团合作方式来提高各自节点的可信度.可信度值曲线示意图表明:本模型较现有模型在抑制网格中恶意节点的活动方面具有更好的效果.根据应用环境的不同需求,对网格经济模型调度算法(DBC)进行改进,分别提出了以时间优化、成本优化和时间成本折衷优化为目的的网格信任调度算法(Trust DBC).模拟实验结果表明:本文算法性能明显优于相应的未考虑信任的调度算法.     

Trust estimation of the semantic web using semantic web clustering

Abstract

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.