文章基本信息

标题：File Detection on Network Traffic Using Approximate Matching
本地全文：下载
作者：Breitinger, Frank ; Baggili, Ibrahim
期刊名称：Journal of Digital Forensics, Security and Law
印刷版ISSN：1558-7215
电子版ISSN：1558-7223
出版年度：2014
卷号：9
期号：2
页码：3
出版社：Association of Digital Forensics, Security and Law
摘要：In recent years, Internet technologies changed enormously and allow faster Internet connections, higher data rates and mobile usage. Hence, it is possible to send huge amounts of data / files easily which is often used by insiders or attackers to steal intellectual property. As a consequence, data leakage prevention systems (DLPS) have been developed which analyze network traffic and alert in case of a data leak. Although the overall concepts of the detection techniques are known, the systems are mostly closed and commercial. Within this paper we present a new technique for network traffic analysis based on approximate matching (a.k.a fuzzy hashing) which is very common in digital forensics to correlate similar files. This paper demonstrates how to optimize and apply them on single network packets. Our contribution is a straightforward concept which does not need a comprehensive configuration: hash the file and store the digest in the database. Within our experiments we obtained false positive rates between 10−4 and 10−5 and an algorithm throughput of over 650 Mbit/s.
关键词：Approximate matching; Bloom filter; mrsh-v2; data loss prevention; network traffic analysis