Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.050427
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 4, 2014.
Abstract: Antivirus software is one of the most widely used tools for detecting and stopping malicious and unwanted files. However, the long term effect of traditional host based antivirus is questionable. Antivirus software fails to detect many modern threats and its increasing complexity has resulted in vulnerabilities that are being exploited by malware. This paper advocates a new model for malware detection on end hosts based on providing antivirus as an in-cloud network service. This model enables identification of malicious and unwanted software by multiple detection engines Respectively,This approach provides several important benefits including better detection of malicious software, enhanced forensics capabilities and improved deployability. Malware detection in cloud computing includes a lightweight, cross-Storge host agent and a network service. In this paper Combines detection techniques, static signatures analyze and Dynamic analysis detection. Using this mechanism we find that cloud- malware detection provides 35% better detection coverage against recent threats compared to a single antivirus engine and a 98% detection rate across the cloud environment.
Safaa Salam Hatem, Dr. Maged H. wafy and Dr. Mahmoud M. El-Khouly, “Malware Detection in Cloud Computing” International Journal of Advanced Computer Science and Applications(IJACSA), 5(4), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050427