Banksafe information stealer detection inside the web browser
RAID'11 Proceedings of the 14th international conference on Recent Advances in Intrusion Detection
A comparative study of malware family classification
ICICS'12 Proceedings of the 14th international conference on Information and Communications Security
Review: Classification of malware based on integrated static and dynamic features
Journal of Network and Computer Applications
Detecting malicious behaviour using supervised learning algorithms of the function calls
International Journal of Electronic Security and Digital Forensics
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In this paper, we focus on rootkits, a special type of malicious software (malware) that operates in an obfuscated and stealthy mode to evade detection. Categorizing these rootkits will help in detecting future attacks against the business community. We first developed a theoretical framework for classifying rootkits. Based on our theoretical framework, we then proposed a new rootkit classification system and tested our system on a sample of rootkits that use inline function hooking. Our experimental results showed that our system could successfully categorize the sample using unsupervised clustering.