社会化网络中恶意代码传播的建模方法与预测技术研究

项目名称： 社会化网络中恶意代码传播的建模方法与预测技术研究

项目编号： No.61303261

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 李书豪

作者单位： 中国科学院信息工程研究所

项目金额： 24万元

中文摘要： 社会化网络中针对恶意代码传播威胁的安全防范具有重要的现实意义，然而社会化网络本身的多样化以及其中恶意代码传播的复杂化给传播态势感知与处理带来巨大挑战。为此，本项目围绕社会化网络恶意代码传播威胁的几个关键问题展开研究，通过深入分析社会化网络的形成与演化过程，构建传播环境模型，通过研究社会化网络用户的业务逻辑与行为特征，构建用户行为模型，通过研究此类恶意代码的传播行为与运行机理，构建基于随机过程理论的跨域传播模型，揭示社会化网络中恶意代码的传播规律，并结合爬虫工具获取真实数据信息，研究此类恶意代码的模拟仿真技术，进而提出一套行之有效的社会化网络恶意代码传播态势预测方法，为构建恶意代码传播态势感知与处理系统提供理论、技术与方法的关键支撑。

中文关键词： 社会化网络；恶意代码；传播模型；模拟仿真；

英文摘要： As defenders, it is with important practical significance how to protect users against the threat from malwares in social networks. However, we face enormous challenges on the prediction of malware propagation trends in social networks, because of the diversification and complexity of social networks and malwares. Therefore, in this project, we will propose several methods and solutions around the propagation threat of social network malwares. Through the deep analysis of the topology of social networks and its evolution, we will model the environment of infection. Through the deep study of the dynamics of user behaviors and the logical vulnerabilities in social networks, we will also build the model of social network users. And then we will formalize a new propagation model based on stochastic process to reveal the general infection process of malwares in social networks. Furthermore, the simulation technology of these malwares is studied, combining with the real data information obtained by social network crawler tools, and then we will design an effective method to predict the propagation trend of a social network malware. The goal for our project is providing for the defense system against social network malwares with key theories, techniques and methods.

英文关键词： Social network；Malware；Propagation model；Simulation；