机会网络下一种采用二审分析法的网络恶意节点检测机制研究

机会网络中一旦有了恶意节点,则会引起网络拥塞甚至系统崩溃。因此,如何检测并拒绝接收恶意节点发出的消息是保证机会网络能够正常顺利运行的一个亟待解决的问题。为解决这一问题,本文提出一种基于“二审分析法”的方式来对节点的恶意特征进行评价,并建立恶意节点黑名单。该算法首先通过主观分析算法对消息节点进行甄别,对无明显恶意特征的节点发送的传输消息进行“放行”,之后对具有恶意特征的嫌疑节点再利用客观分析算法进一步判断,并将满足条件的节点加入黑名单。正常节点不接收黑名单中各节点发送的消息,以此来抵御恶意节点的注入式攻击。该算法兼顾机会网络节点间的传输机会和节点内部资源,提高了节点恶意性的分析效率。同时提出“有效报文投递率”“有效传输延时”“有效网络开销”等概念,即各项统计指标不再纳入真实恶意节点产生的数据,通过各项“有效指标”,将更准确地对数据进行观察。

Research on a Malicious Node Detection Mechanism Based on Reviewing Tow Times Analysis in Opportunistic Networks

Once there are malicious nodes in an opportunistic network,it will cause network congestion or even system crash.Therefore,how to detect and refuse to receive messages from malicious nodes has become an urgent problem to ensure that the opportunistic network can operate normally and smoothly.In order to solve this problem,this paper proposes a method based on“Er-Shen analysis method”to evaluate the malicious characteristics of nodes and establish a blacklist of malicious nodes.This algorithm first screens message nodes through a subjective analysis algorithm,and"passes"the transmission messages sent by nodes with no obvious malicious characteristics,and then uses objective analysis algorithms to further judge suspect nodes with malicious characteristics,and blacklists nodes that meet the conditions.Normal nodes do not receive messages sent by nodes in the blacklist to defend against injection attacks by malicious nodes.The algorithm takes into account both the transmission opportunities between nodes and the internal resources of the nodes in the opportunistic network,and improves the analysis efficiency of node maliciousness.At the same time,the concepts of“effective message delivery rate”,“effective transmission delay”,and“effective network overhead”are proposed,that is,various statistical indicators are no longer included in the data generated by real malicious nodes,and the data can be observed more accurately through various“effective indicators”.