一种基于挤压的个人电脑闯入探测器的设计与实现

Weidong Cui, R. Katz, Wai-tian Tan
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引用次数: 51

摘要

越来越多的恶意软件,如蠕虫、间谍软件和广告软件,威胁着个人和商业计算。被入侵系统的远程控制机器人网络正在迅速增长。在本文中,我们解决了针对个人电脑的未知恶意软件入侵的自动检测问题。我们开发了一个基于主机的系统BINDER(入侵检测器),通过捕获用户无意的恶意出站连接(称为挤出)来检测入侵。为了推断用户意图,BINDER在流程级别将出站连接与用户驱动的输入关联起来,假设用户驱动的输入隐含了用户意图。因此,BINDER可以检测大量未知的恶意软件,如蠕虫,间谍软件和广告软件,而不需要签名。我们已经成功地使用BINDER在日常使用的计算机上检测真实世界的间谍软件,并在受控的测试台上检测电子邮件蠕虫,假阳性非常小
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Design and implementation of an extrusion-based break-in detector for personal computers
An increasing variety of malware, such as worms, spyware and adware, threatens both personal and business computing. Remotely controlled bot networks of compromised systems are growing quickly. In this paper, we tackle the problem of automated detection of break-ins caused by unknown malware targeting personal computers. We develop a host based system, BINDER (Break-IN DEtectoR), to detect break-ins by capturing user unintended malicious outbound connections (referred to as extrusions). To infer user intent, BINDER correlates outbound connections with user-driven input at the process level under the assumption that user intent is implied by user-driven input. Thus BINDER can detect a large class of unknown malware such as worms, spyware and adware without requiring signatures. We have successfully used BINDER to detect real world spyware on daily used computers and email worms on a controlled testbed with very small false positives
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