Light-weight Trust-enhanced On-demand Multi-path Routing in Mobile Ad Hoc Networks
Light-weight Trust-enhanced On-demand Multi-path Routing in Mobile Ad Hoc Networks
复制标题
移动自组织网络中的轻量级信任增强型按需多路径路由
DOI：
10.1016/j.jnca.2015.12.005
复制
发表时间：
2016-02
影响因子：
8.7
通讯作者：
Edwin Sha
中科院分区：
文献类型：
--
作者：
Hui Xia;Jia Yu;Cheng-liang Tian;Zhen-kuan Pan;Edwin Sha
移动自组织网络（manet）最初是为协作环境而设计的，由于其固有的特性，容易受到各种各样的攻击。可以引入信任来在某种程度上解决此安全问题。本文从信任的概念出发，抽象了一个去中心化的信任推理模型，其中实体对邻居的信任构成了该模型的基本构件。基于利益实体的历史行为，纳入多维信任属性，从多个角度反映信任关系的复杂性。采用基于熵权测度的模糊层次分析法计算属性权向量。信任推理框架以很小的额外开销提供了相当高的安全性，可以将其合并到任何路由协议中。本文将标准的Ad hoc按需多路径距离矢量协议（AOMDV）扩展为基础路由协议来评估该模型。提出的轻量级信任增强路由协议TeAOMDV （lightweight trust-enhanced routing protocol）提供了一种可行的方法来选择不包含untrust实体的最优双向可信路由，而不是最短路由，从而减轻了这些实体的损害影响。它是轻量级的，因为信任框架只使用被动的和局部的监控信息来评估利益实体的行为，并将其转化为对信任的估计，消耗有限的计算资源。此外，新提出的数据驱动路由维护机制降低了路由开销和路由发现频率。仿真结果表明，所提出的路由方案具有较好的抗灰洞攻击和黑洞攻击性能，在报文投递率、路由报文开销、路由发现频率和恶意节点检测等方面均有提高。最后，作为信任模型的扩展，利用信任评估数据序列，提出了一种基于系统云灰色模型和马尔可夫随机链理论的改进SCGM(1,1)-马尔可夫链预测方法，用于预测实体的信任水平，为未来决策提供依据。
Mobile ad hoc networks (MANETs) are originally designed for a cooperative environment, which are vulnerable to a wide variety of attacks due to their intrinsic characteristics. Trust can be introduced to address this security issue at some level. In this paper, we focus on the concept of trust and abstract a decentralized trust inference model, where the trust an entity has for a neighbor forms the basic building block of this model. Basing on the interest entity׳s historical behaviors, multi-dimensional trust attributes are incorporated to reflect trust relationship׳s complexity in various angles. The weight vector of attributes is calculated by fuzzy AHP scheme based on entropy weight measure. The trust inference framework provides the considerable security with an additional small overhead, which can be incorporated into any routing protocol. In this paper, the standard Ad hoc On-demand Multi-path Distance Vector protocol (AOMDV) is extended as the base routing protocol to evaluate this model. The proposed light-weight trust-enhanced routing protocol (TeAOMDV) can provide a feasible approach to choose an optimal two-way trusted route without containing the untrust worthy entities instead of the shortest route, thus mitigate the impairment effects from such entities. It is light-weight in the sense that the trust framework uses only passive and local monitoring information to evaluate the behaviors of an interest entity which is translated to an estimate of the trust, consumes limited computational resource. Moreover, the new proposed data-driven route maintenance mechanism reduces routing overhead and route discovery frequency. The simulations show that the proposed routing scheme behaves better in attack resistance (i.e., gray-hole attack and black-hole attack), and makes an improvement on the packets delivery ratio, routing packets overhead, route discovery frequency and malicious node detection. Finally, as an extension of the trust model, by utilizing the trust assessment data sequence, we propose an improved SCGM(1,1)-Markov chain prediction method based on the system cloud gray model and Markov stochastic chain theory to forecast entity׳s trust level for future decision making.
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DOI：
10.1016/j.peva.2007.04.001
发表时间：
2008-02
期刊：
Perform. Evaluation
影响因子：
--
作者：
Zhengqiang Liang;Weisong Shi
通讯作者：
Zhengqiang Liang;Weisong Shi
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影响因子：
8.7
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DOI：
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发表时间：
2012-07
期刊：
IET Inf. Secur.
影响因子：
--
作者：
Ningrinla Marchang;R. Datta
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Ningrinla Marchang;R. Datta
DOI：
10.1007/978-3-642-33260-9_6
发表时间：
2012-09
期刊：
--
影响因子：
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作者：
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DOI：
10.1109/tpds.2013.116
发表时间：
2014-05-01
影响因子：
5.3
作者：
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Cho, Jin-Hee