A Survey on Visualization-Based Malware Detection

作     者：Ahmad Moawad Ahmed Ismail Ebada Aya M.Al-Zoghby 

作者机构：Computer Science DepartmentFaculty of Computers and Artificial IntelligenceDamiettaNew Damietta34517Egypt 

出 版 物：《Journal of Cyber Security》 (网络安全杂志（英文）)

年 卷 期：2022年第4卷第3期

页      面：153-168页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Malware detection malware image malware classification visualization-based detection survey 

摘      要：In computer security,the number of malware threats is increasing and causing damage to systems for individuals or organizations,necessitating a new detection technique capable of detecting a new variant of malware more efficiently than traditional anti-malware *** antimalware software cannot detect new malware variants,and conventional techniques such as static analysis,dynamic analysis,and hybrid analysis are time-consuming and rely on domain ***-based malware detection has recently gained popularity due to its accuracy,independence from domain experts,and faster detection ***-based malware detection uses the image representation of the malware binary and applies image processing techniques to the *** paper aims to provide readers with a comprehensive understanding of malware detection and focuses on visualization-based malware detection.