Abstract
Traditional malware detection techniques, such as signature-based detection and traditional antivirus software, are not beneficial for detecting many recent malware threats. In this paper, we propose a novel malware detection technique, API call transition matrix-based malware detection (ACTM), that efficiently detects malware based on their runtime behavior. We find that the ACTM technique performs better and detects malware with approximately 95.23% accuracy. ACTM can find applications in designing real-time malware detection when an enterprise network security system is concerned.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
