基于社区的恶意软件免疫策略

Wei Yang, Li Zhang, Teng Chen, Yu Yao
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引用次数: 0

摘要

近年来,安全威胁事件频发,尤其是恶意软件的大规模传播给个人和国家带来了巨大的损失。本文认为网络节点具有形成社区的特征。针对社区内信息传播快、社区间信息传播慢的特点,提出了基于社区的恶意软件免疫策略。为了以最快的速度和最低的代价控制恶意代码的爆发,提出了一种基于K-shell和标签传播算法的具体社区检测方法,并提出了关键节点选择算法。实验表明,与传统免疫策略相比,该方法可以以最小的成本获得最大的免疫效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Community-based Malware Immunization Strategy
In recent years, security threats have occurred frequently, especially the large-scale spread of malware has brought huge losses to individuals and the country as a whole. This paper considers the nodes of the network have the feature of forming a community. A community-based malware immunization strategy is proposed according to the characteristics that information spread quickly within the community and spread slowly between communities. A concrete community detection method is proposed based on the K-shell and the label propagation algorithm, as well as key node selection algorithm is proposed in order to control the outbreak of malicious code with the fastest speed and at the lowest cost. The experiments demonstrate that the proposed approach can achieve maximum immunity with minimal cost comparing to classical immunization strategies.
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