יובל אלוביץ

אקדמי בכיר

F-sign

Automatic, function-based signature generation for malware

Asaf Shabtai, Eitan Menahem, Yuval Elovici

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.

שפת פרסום אנגלית
דפים 494-508
כתב עת IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
כרך 41
נושא מספר 4
סטטוס פרסום פורסם - 01.01.2011
5585792

Keywords

Automatic signature generation (ASG)
malware
malware filtering

ASJC Scopus subject areas

Control and Systems Engineering
Software
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering
גישה למסמך
10.1109/TSMCC.2010.2068544
קבצים וקישורים אחרים
Link to publication in Scopus