TY - GEN
T1 - An efficient approach for advanced malware analysis using memory forensic technique
AU - Rathnayaka, Chathuranga
AU - Jamdagni, Aruna
PY - 2017
Y1 - 2017
N2 - ![CDATA[Static analysis in malware analysis has been complex due to string searching methods. Forensic investigation of the physical memory or memory forensics provides a comprehensive analysis of malware, checking traces of malware in malware dumps that have been created while running in an operating system. In this study, we propose efficient and robust framework to analyse complex malwares by integrating both static analysis techniques and memory forensic techniques. The proposed framework has evaluated two hundred real malware samples and achieved a 90% detection rate. These results have been compared and verified with the results obtained from www.virustotal.com, which is online malware analysis tool. Additionally, we have identified the sources of many malware samples.]]
AB - ![CDATA[Static analysis in malware analysis has been complex due to string searching methods. Forensic investigation of the physical memory or memory forensics provides a comprehensive analysis of malware, checking traces of malware in malware dumps that have been created while running in an operating system. In this study, we propose efficient and robust framework to analyse complex malwares by integrating both static analysis techniques and memory forensic techniques. The proposed framework has evaluated two hundred real malware samples and achieved a 90% detection rate. These results have been compared and verified with the results obtained from www.virustotal.com, which is online malware analysis tool. Additionally, we have identified the sources of many malware samples.]]
KW - computer networks
KW - malware (computer software)
UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:45128
U2 - 10.1109/Trustcom/BigDataSE/ICESS.2017.365
DO - 10.1109/Trustcom/BigDataSE/ICESS.2017.365
M3 - Conference Paper
SN - 9781509049066
SP - 1145
EP - 1150
BT - 2017 IEEE Trustcom/BigDataSE/ICESS: Proceedings of the 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, the 11th IEEE International Conference on Big Data Science and Engineering, and the 14th IEEE International Conference on Embedded Software and Systems, 1-4 August 2017, Sydney, Australia
PB - IEEE
T2 - IEEE International Conference on Trust_Security and Privacy in Computing and Communications
Y2 - 1 August 2017
ER -