Malware Detection Based on Hybrid Signature Behaviour Application Programming Interface Call Graph | Science Publications

American Journal of Applied Sciences

Mohd A. Maarof¹  Ahmed H. Osman¹  Ammar A.E. Elhadi¹ 

关键词: Malware detection;    API call graph;    framework;   

DOI  :  10.3844/ajassp.2012.283.288

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: A malware is a program that has malicious intent. Nowadays, malwareauthors apply several sophisticated techniques such as packing and obfuscation to avoid malwaredetection. That makes zero-day attacks and false positives the most challenging problems in themalware detection field. Approach: In this study, the static and dynamic analysis techniques that areused in malware detection are surveyed. Static analysis techniques, dynamic analysis techniques andtheir combination including Signature-Based and Behaviour-Based techniques are discussed. Results: In addition, a new malware detection framework is proposed. Conclusion: The proposed frameworkcombines Signature-Based with Behaviour-Based using API graph system. The goal of the proposedframework is to improve accuracy and scan process time for malware detection.

【 授权许可】

Unknown