基于社交网络的蠕虫传播与建模研究
发布时间：2018-09-12 20:50
【摘要】：20世纪末,社交网络的出现迅速吸引了大量的因特网用户,这类提供实时交互功能的网站改变了人们沟通和交流的方式,创造了巨大的社会和经济价值。社交网络规模日益增长的同时也引起了网络黑客的高度关注,这些攻击者利用网站中存在的漏洞发起各类网络攻击,其中XSS蠕虫是社交网络上重大的威胁之一。与传统网络蠕虫相比,XSS蠕虫并不具备主动攻击性,而正是由于XSS蠕虫传播的被动性,人们往往会忽视其危害性,以致蠕虫爆发后造成严重的后果。 为了研究XSS蠕虫在社交网络中的传播规律,本文提出了一种利用网络拓扑矩阵与节点状态向量进行逻辑迭代计算的方法来构建蠕虫传播模型。其中网络拓扑通过以下两种途径获取：一是利用网络爬虫程序抓取人人网上用户间的好友关系构建网络拓扑,二是通过对BA算法和社交网络拓扑特性的研究,提出了改进的BA算法以生成不同规模的网络拓扑。在研究XSS蠕虫传播过程中网络用户状态的变换规律时,利用线性向量记录用户节点在每个时间点上所处的状态,并通过网络拓扑矩阵与节点状态向量的逻辑运算来模拟实现蠕虫的传播过程。 通过对比分析人人网和BA改进算法生成网络的拓扑数据,验证了BA改进算法的有效性。与此同时,针对在线用户数量、用户安全意识和不同免疫强度对蠕虫传播的影响进行了大量仿真实验,实验结果表明本文提出的蠕虫传播模型能真实地反映XSS蠕虫在社交网络中的传播过程,为相关领域的研究提供了有力的理论支撑。
[Abstract]:At the end of the 20th century, the emergence of social networks rapidly attracted a large number of Internet users. Such websites, which provide real-time interactive functions, have changed the way people communicate and communicate, and created enormous social and economic value. At the same time, the growing scale of social networks has also attracted the attention of network hackers. These attackers take advantage of the vulnerabilities in websites to launch various network attacks, among which the XSS worm is one of the major threats to social networks. Compared with the traditional network worms, the XSS worms are not active and aggressive. However, because of the passive propagation of the XSS worms, people often ignore the harmfulness of the worms, resulting in serious consequences after the outbreak of the worms. In order to study the propagation law of XSS worm in social network, this paper proposes a method to construct worm propagation model by using network topology matrix and node state vector for logical iterative calculation. The network topology is obtained by the following two ways: one is to use the crawler program to capture the friend relationship between the users on the human network to construct the network topology, the other is to study the BA algorithm and the characteristics of the social network topology. An improved BA algorithm is proposed to generate network topologies of different scales. In this paper, we use linear vector to record the states of user nodes at each point in time when we study the transformation rules of network user states during the propagation of XSS worm. The worm propagation process is simulated by the logical operation of network topology matrix and node state vector. The effectiveness of the improved BA algorithm is verified by comparing and analyzing the topology data generated by the artificial network and the improved BA algorithm. At the same time, a large number of simulation experiments have been carried out on the influence of the number of online users, the security awareness of users and the different immune intensity on the propagation of worms. The experimental results show that the worm propagation model presented in this paper can truly reflect the propagation process of XSS worms in social networks and provide a powerful theoretical support for the research of related fields.
【学位授予单位】：北京化工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.08
本文编号：2240184
[Abstract]:At the end of the 20th century, the emergence of social networks rapidly attracted a large number of Internet users. Such websites, which provide real-time interactive functions, have changed the way people communicate and communicate, and created enormous social and economic value. At the same time, the growing scale of social networks has also attracted the attention of network hackers. These attackers take advantage of the vulnerabilities in websites to launch various network attacks, among which the XSS worm is one of the major threats to social networks. Compared with the traditional network worms, the XSS worms are not active and aggressive. However, because of the passive propagation of the XSS worms, people often ignore the harmfulness of the worms, resulting in serious consequences after the outbreak of the worms. In order to study the propagation law of XSS worm in social network, this paper proposes a method to construct worm propagation model by using network topology matrix and node state vector for logical iterative calculation. The network topology is obtained by the following two ways: one is to use the crawler program to capture the friend relationship between the users on the human network to construct the network topology, the other is to study the BA algorithm and the characteristics of the social network topology. An improved BA algorithm is proposed to generate network topologies of different scales. In this paper, we use linear vector to record the states of user nodes at each point in time when we study the transformation rules of network user states during the propagation of XSS worm. The worm propagation process is simulated by the logical operation of network topology matrix and node state vector. The effectiveness of the improved BA algorithm is verified by comparing and analyzing the topology data generated by the artificial network and the improved BA algorithm. At the same time, a large number of simulation experiments have been carried out on the influence of the number of online users, the security awareness of users and the different immune intensity on the propagation of worms. The experimental results show that the worm propagation model presented in this paper can truly reflect the propagation process of XSS worms in social networks and provide a powerful theoretical support for the research of related fields.
【学位授予单位】：北京化工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.08
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