Title : 
F-Sign: Automatic, Function-Based Signature Generation for Malware
         
        
            Author : 
Shabtai, Asaf ; Menahem, Eitan ; Elovici, Yuval
         
        
            Author_Institution : 
Dept. of Inf. Syst. Eng., Ben-Gurion Univ., Beer-Sheva, Israel
         
        
        
        
        
            fDate : 
7/1/2011 12:00:00 AM
         
        
        
        
            Abstract : 
In this research, we present a new method, termed F-Sign, for automatic extraction of unique signatures from malware files. F-Sign is primarily intended for high-speed network traffic filtering devices that are based on deep-packet inspection. Malicious executables are analyzed using two approaches: disassembly, utilizing IDA-Pro, and the application of a dedicated state machine in order to obtain the set of functions comprising the executables. The signature extraction process is based on a comparison with a common function repository. By eliminating functions appearing in the common function repository from the signature candidate list, F-Sign can minimize the risk of false-positive detection errors. To minimize false-positive rates even further, F-Sign proposes intelligent candidate selection using an entropy score to generate signatures. Evaluation of F-Sign was conducted under various conditions. The findings suggest that the proposed method can be used for automatically generating signatures that are both specific and sensitive.
         
        
            Keywords : 
digital signatures; error detection; finite state machines; invasive software; F-sign; IDA-Pro; automatic extraction; automatic signature generation; common function repository; deep packet inspection; entropy score; false positive detection error; function-based signature generation; high speed network traffic filtering device; intelligent candidate selection; malware; signature candidate list; signature extraction process; state machine; Binary codes; Grippers; Libraries; Malware; Monitoring; Real time systems; Software; Automatic signature generation (ASG); malware; malware filtering;
         
        
        
            Journal_Title : 
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
         
        
        
        
        
            DOI : 
10.1109/TSMCC.2010.2068544