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.     

基于多维度的P2P网络信任管理机制

针对分布式点对点(P2P)网络中的信任管理问题,提出了一种多维度的信任管理机制。它运用直接信任评估和间接信任评估方法,依据各用户的行为来判定系统中用户的可信任程度,从而避免因为恶意用户的恶意反馈对网络造成的负面影响。在Bad Mouthing和on-off攻击场景下与EigenTrust方法进行对比,所提出的方法取得了较好的有效传输率(SRT),表明该机制能够有效地抑制恶意用户的行为。     

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).     

Combining search and trust models in unstructured peer-to-peer networks

Effectiveness of Peer-to-Peer (P2P) systems highly depends on efficiency and scalability of their search algorithms. Moreover, managing trust is a key issue for wide acceptance of P2P computing. Surprisingly, the majority of the available trust systems ignore the underlying search algorithm and assume it is preexisting. We claim that combining search and trust systems yields significant performance gains in terms of network traffic and query success rate. In this paper, we propose a robust and efficient trust based search framework for unstructured P2P networks. Our framework maintains limited size routing indexes combining search and trust data to guide queries to most reputable nodes. By dynamically selecting reputable nodes as score managers, our scheme tracks the reputation of participating peers. In an alternative approach, we aggregate partial reputation values obtained from reverse query paths to introduce a low overhead method for estimating reputation scores of peers. Through P2P network simulation experiments, we find significant performance gains in using our framework.     

Adaptive searching and replication of images in mobile hierarchical peer-to-peer networks

Due to the limitation of resources in mobile handheld devices and bandwidth constraints in wireless networks, it is important to efficiently manage image content and traffic to improve network throughput and response time. The efficient distribution of images in wireless networks is based on many parameters like the quality of service requirement, available bandwidth, restricted memory and diverse user profiles. We consider digital images as data objects accessed in a hierarchical mobile ad-hoc peer-to-peer network, referred as M-P2P. Our objective is to optimize the number of replicas of images in such a network architecture based on the resource limitations of the requesting peers equipped with miniature mobile devices as well as of wireless constraints in mobile ad-hoc networks (MANET). While replicating images, fragments of different resolution and their residues are used to optimize the traffic in the network and to decrease the search turnaround time. We call this replication algorithm as Ada-Rep. Performance evaluation is done by simulating Ada-Rep, base replication and uniform replication methods to evaluate parameters such as response time, failure rate, memory usage, traffic etc. Our results prove the efficiency and better performance of Ada-Rep.     

Adaptive searching and replication of images in mobile hierarchical peer-to-peer networks

Due to the limitation of resources in mobile handheld devices and bandwidth constraints in wireless networks, it is important to efficiently manage image content and traffic to improve network throughput and response time. The efficient distribution of images in wireless networks is based on many parameters like the quality of service requirement, available bandwidth, restricted memory and diverse user profiles. We consider digital images as data objects accessed in a hierarchical mobile ad-hoc peer-to-peer network, referred as M-P2P. Our objective is to optimize the number of replicas of images in such a network architecture based on the resource limitations of the requesting peers equipped with miniature mobile devices as well as of wireless constraints in mobile ad-hoc networks (MANET). While replicating images, fragments of different resolution and their residues are used to optimize the traffic in the network and to decrease the search turnaround time. We call this replication algorithm as Ada-Rep. Performance evaluation is done by simulating Ada-Rep, base replication and uniform replication methods to evaluate parameters such as response time, failure rate, memory usage, traffic etc. Our results prove the efficiency and better performance of Ada-Rep.     

Choquet fuzzy integral-based hierarchical networks for decisionanalysis

A Choquet fuzzy integral-based approach to hierarchical network implementation is investigated. In this approach, we generalized the fuzzy integral as an excellent component for decision analysis. The generalization involves replacing the max (or min) operator in information aggregation with a fuzzy integral-based neuron, resulting in increased flexibility. The characteristics of the Choquet fuzzy integral are studied and a network-based decision-analysis framework is proposed. The trainable hierarchical network can be implemented utilizing the fuzzy integral-based neurons and connectives. The training algorithms are derived and several examples given to illustrate the behaviors of the networks. Also, we present a decision making experiment using the proposed network to learn appropriate functional relationships in the defective numeric fields detection domain     

DGTM: a dynamic grouping based trust model for mobile peer-to-peer networks

The special characteristics of the mobile environment, such as limited bandwidth, dynamic topology, heterogeneity of peers, and limited power, pose additional challenges on mobile peer-to-peer (MP2P) networks. Trust management becomes an essential component of MP2P networks to promote peer transactions. However, in an MP2P network, peers frequently join and leave the network, which dynamically changes the network topology. Thus, it is difficult to establish long-term and effective trust relationships among peers. In this paper, we propose a dynamic grouping based trust model (DGTM) to classify peers. A group is formed according to the peers’ interests. Within a group, mobile peers share resources and tend to keep stable trust relationships. We propose three peer roles (super peers, relay peers, and ordinary peers) and two novel trust metrics (intragroup trust and intergroup trust). The two metrics are used to accurately measure the trust between two peers from the same group or from different groups. Simulations illustrate that our proposed DGTM always achieves the highest successful transaction rate and the best communication overhead under different circumstances.     

Enhancing peer-to-peer collaboration using trust

Distributed systems generally require their component parts to interact cooperatively, in order for the system as a whole to function effectively. For any given activity, there are typically several alternative components that have the required capabilities. In decentralised systems, where there is no overarching control, individual components are responsible for selecting other components with which to cooperate. However, the candidate components may be unreliable or dishonest, and are typically locally controlled. Such decentralised systems can be viewed as multi-agent systems, comprising autonomous agents that must cooperate for the system to be effective. Peer-to-peer (P2P) systems are a subclass of decentralised distributed systems, in which not only is there no overarching control, but neither is there any hierarchy of control, power, or responsibly among the system components. Selecting appropriate peers to cooperate with is a challenging problem, since the candidate peers are autonomous and may be unreliable or dishonest. Peers need a mechanism for task delegation that takes the uncertainly of interactions into account. In this paper we present a mechanism, called Mdt-r, that enables peers to delegate activities appropriately, using trust and the recommendations of other peers to meet individual preferences, such as minimising risk and maximising quality.     

Enhancing peer-to-peer collaboration using trust

Distributed systems generally require their component parts to interact cooperatively, in order for the system as a whole to function effectively. For any given activity, there are typically several alternative components that have the required capabilities. In decentralised systems, where there is no overarching control, individual components are responsible for selecting other components with which to cooperate. However, the candidate components may be unreliable or dishonest, and are typically locally controlled. Such decentralised systems can be viewed as multi-agent systems, comprising autonomous agents that must cooperate for the system to be effective. Peer-to-peer (P2P) systems are a subclass of decentralised distributed systems, in which not only is there no overarching control, but neither is there any hierarchy of control, power, or responsibly among the system components. Selecting appropriate peers to cooperate with is a challenging problem, since the candidate peers are autonomous and may be unreliable or dishonest. Peers need a mechanism for task delegation that takes the uncertainly of interactions into account. In this paper we present a mechanism, called Mdt-r, that enables peers to delegate activities appropriately, using trust and the recommendations of other peers to meet individual preferences, such as minimising risk and maximising quality.     

基于递阶遗传算法模糊加权神经网络的模糊规则自动获取

针对模糊规则的自动获取一直是模糊系统的一个瓶颈问题,提出一种基于递阶结构的混合编码遗传算法与进化规划相结合的模糊加权神经网络学习新算法,利用该算法同时优化模糊加权神经网络的结构和参数,最后说明了从网络中提取模糊规则的方法,从而自动获得最优的模糊规则。分析和实验结果表明,本文方法在规则提取和分类准确性等方面比其他方法更好。     

基于模糊理论的行为信任评估研究

开放网络环境中的信任分为身份信任和行为信任两种,行为信任具有主观性和不确定性的特点,其关注的是更广泛意义上的可信性,网络实体可以根据过去的交互经验动态更新相互之间的信任关系.讨论了使用模糊理论评估行为信任的合理性,提出了一种基于模糊理论的信任评估方法,最后用一个场景实验验证了该方法.     

基于模糊集合的完整性信任度评估模型

完整性度量是可信计算得以实现的一项重要技术。根据影响操作系统完整性的内核模块、二进制可执行文件等因素,通过定义直接信任度、间接信任度和综合信任度等计算公式构建了一个操作系统的完整性信任度评估模型,该模型利用模糊集合理论将完整性度量化为[0,1]之间的具体数值,并根据隶属函数将操作系统的信任度划分为四个信任等级。该模型改变了原有完整性度量中一致执行、不一致停止的二值状态,为远程验证者提供较为精确的操作系统完整性度量值,提高了系统的可用性。仿真实验结果表明该模型较客观地提供了操作系统的完整性信息。     

一种综合的P2P网络信任模型

安全有效的信任模型是保证P2P 系统高效、稳定的关键技术之一。介绍一种适用于P2P 网络的综合信任模型,它参考了社会网络中信任关系的建立方法,从两个角度来计算节点的综合可信度。该模型中引入了非对称加密等安全机制,通过分析与仿真证明该模型能有效地抑制冒名和诋毁等非法行为,具有较强的安全性。     

可信计算信任模型的模糊评估方法研究

基于可信计算中可信性影响因素,详细地讨论了基于模糊集合理论的可信计算信任模型的评估方法。把模糊逻辑推理同信任传递结合起来,采用基于相似度的加权模糊推理方法得到委托实体的可信度,评价信任模型的可信性,为可信计算信任评估提供了一种新的思路。     

基于模糊模拟的主观信任评价模型研究

通过对开放网络环境中主观信任评价方法的讨论,考虑到主观信任的模糊性,提出以可信性理论为基础的主观信任量化表述与评价方法,并给出了主体信任属性评价值为模糊变量情形下主观信任可信性的模拟计算方法。实例分析表明,该方法对主观信任评价是可行和有效的。     

基于模糊理论的主观信任评价模型的研究

针对开放式网络环境中信任的主观性、不确定性等特点, 提出了一个基于模糊理论的主观信任评价模型。该模型运用模糊理论得出节点间的综合信任评价的计算式, 并在信任的计算中引入时间因子、对不诚信节点的约束机制, 利用贴近度反求权重计算综合信任值, 最后利用模糊等价关系实现信任值的聚类分析。通过仿真实验结果分析, 证明了该模型具有有效性和可行性, 并通过仿真实验比较, 验证了该模型能够客观地反映出接近真实的情况。     

Contention-based performance evaluation of multidimensional range search in peer-to-peer networks

Performance evaluation of peer-to-peer search techniques has hitherto been based on simple performance metrics, such as message hop counts and total network traffic, mostly disregarding the inherently concurrent nature of peer-to-peer networks, where contention may arise. This paper is concerned with quantifying the effects of contention in P2P networks, focusing on networks for multidimensional range search. We evaluate peer-to-peer networks derived from recently proposed works, introducing two novel metrics related to concurrency and contention, namely responsiveness and throughput. Our results highlight the impact of contention on these networks, and demonstrate that some studied networks do not scale in the presence of contention. Also, our results indicate that certain P2P network properties believed to be desirable (e.g. even data distribution or uniform peer access) may not be as critical as previously believed.