Towards a Forensic Analysis for Multimedia Communication Services

D. Geneiatakis, A. Keromytis
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引用次数: 3

Abstract

No matter how robust the employed security mechanisms are malicious users or attackers will always find a way to bypass them. In addition, National Institute of Security and Technology mentions "In conjunction with appropriate tools & procedures, audit trail can assist in detecting security violation and flaws in applications". Until now, in Multimedia Communication Services (MCS), such as Voice over IP, audit trails are not utilized in security audits due to (a) the lack of the appropriate analysis tools and (b) privacy restrictions. In this paper we report on the analysis of MCS audit trail by employing a novel method for identifying "uncommon" traffic indicating non normal behaviour that does not violate users’ privacy. We rely on entropy theory and the notion of "itself information" to quantify the randomness of specific message segments, and we also introduce the term "actual itself information" for the assessment of entire message randomness. To protect users’ privacy we hash audit trail’s data. For evaluating the applicability of our proposed method we utilize an audit trail of a real MCS provider published by honey pot project. Initial outcomes show the feasibility of employing such a method to recognize "uncommon" traffic, recorded in MCS audit trail.
面向多媒体通信服务的取证分析
无论所采用的安全机制多么健壮,恶意用户或攻击者总能找到绕过它们的方法。此外,国家安全与技术研究所提到“结合适当的工具和程序,审计跟踪可以帮助检测应用程序中的安全违规和缺陷”。到目前为止,在多媒体通信服务(MCS)中,如IP语音,由于(a)缺乏适当的分析工具和(b)隐私限制,审计跟踪没有用于安全审计。在本文中,我们报告了对MCS审计跟踪的分析,采用了一种新的方法来识别表明不侵犯用户隐私的非正常行为的“不寻常”流量。我们依靠熵理论和“自身信息”的概念来量化特定消息段的随机性,并引入术语“实际自身信息”来评估整个消息的随机性。为了保护用户的隐私,我们对审计跟踪数据进行哈希处理。为了评估我们提出的方法的适用性,我们使用了一个由蜜罐项目发布的真实MCS提供商的审计跟踪。初步结果表明,采用这种方法识别记录在MCS审计跟踪中的“不常见”流量是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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