期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2012
卷号：5
期号：2
出版社：SERSC
摘要：The sheer volume of new malware found each day is growing at an exponential pace. Centralized systems that collect all malware samples to central severs can cause problems of single point of failure as well as processing bottlenecks. Previous works on distributed and scalable malware analysis are mainly applied for specific or simple malware. This paper presents CCS, a collaborative online malware analysis system which is applied for various malware and well scalable. Each sensors in CCS analysis their own malware samples accurately in-situ and then CCS aggregates those analyses among sensors in a load-balance way. We implemented a proof-of-concept version of CCS and performed experiments with 917 real-world malware samples; preliminary results from our evaluation confirm that CCS has comparable performance with centralized system, but much better scalability, and is approximately consistent with the result of AV scanners
关键词：collaborative malware analysis; malware behaviors; local analysis; global ;aggregation; signature generation
