@inproceedings{6209d14d39cb4b0ead5d1bdd138d73f1,
title = "Mal-ONE: A unified framework for fast and efficient malware detection",
abstract = "With continuous increase rate of malware growth, detecting malware using conventional, signature-based method has failed to detect new or unknown malware. The new proposed framework is able to detect evasive malware and integrate key static and dynamic features to detect malware more accurately and efficiently. Our early experiments, based on 1603 malware samples, showed that the proposed system can analyze malware with the rate of about 144 seconds per binary code analyzed. Mal-One framework exhibits comparable overall time taken to detect and analyze the binary code to determine whether a binary code is malware or benign.",
keywords = "malware, malware analysis, malware detection, unified framework",
author = "Charles Lim and Kalamullah Ramli",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014 ; Conference date: 19-08-2014 Through 21-08-2014",
year = "2015",
month = jan,
day = "15",
doi = "10.1109/TIME-E.2014.7011581",
language = "English",
series = "Proceedings of 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "Proceedings of 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014",
address = "United States",
}