点对点网络中的被动蠕虫和恶意软件检测

Sahar Fahimian, Amirvala Movahed, M. Kharrazi
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引用次数: 2

摘要

今天,P2P网络负责互联网上的大量流量,因为许多互联网用户使用这种网络进行内容分发。同时,P2P网络容易受到Internet蠕虫等安全威胁,易于传播。互联网蠕虫和更普遍的恶意软件是网络安全社区主要关注的问题。在野外有许多不同类型的蠕虫,主要是根据它们如何发现和感染它们的新受害者(即主动,被动等)来分类的。本文基于P2P网络中文件的普及,研究了一种检测被动蠕虫和恶意软件的新方法。作为我们调查的一部分,我们在12天的时间内抓取Gnutella P2P网络,收集文件名和文件流行度统计数据。然后,我们能够提取高度流行的文件,并识别其中的蠕虫/恶意软件文件具有很高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Passive Worm and Malware Detection in Peer-to-Peer Networks
Today P2P networks are responsible for a large amount of traffic on the Internet, as many Internet users employ such networks for content distribution. At the same time, P2P networks are vulnerable to security threats such as Internet worms and facilitate their propagation. Internet worms and more generally malware are a major concern to the network security community. There are many different type of worms in the wild, mostly categorized based on how they find and infect their new victims (i.e. active, passive, etc.). In this paper, we investigate a new approach for detecting passive worms and malware in P2P networks based on the popularity of files in the network. As part of our investigation, we crawl the Gnutella P2P network over a 12 day period collecting file names and file popularity statistics. We are then able to extract the highly popular files and identify worm/malware files within them with high accuracy.
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