Intelligent file scoring system for malware detection from the gray list

Currently, the most significant line of defense against malware is anti-virus products which focus on authenticating valid software from a white list, blocking invalid software from a black list, and running any unknown software (i.e., the gray list) in a controlled manner. The gray list, containing unknown software programs which could be either normal or malicious, is usually authenticated or rejected manually by virus analysts. Unfortunately, along with the development of the malware writing techniques, the number of file samples in the gray list that need to be analyzed by virus analysts on a daily basis is constantly increasing. In this paper, we develop an intelligent file scoring system (IFSS for short) for malware detection from the gray list by an ensemble of heterogeneous base-level classifiers derived by different learning methods, using different feature representations on dynamic training sets. To the best of our knowledge, this is the first work of applying such e...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Yanfang Ye, Tao Li, Qingshan Jiang, Zhixue Han, Li Wan
• Keywords: Gray List, KDD 2009, Malware, Virus Analysts