| Title | Detection Efficiency of Static Analyzers against Obfuscated Android Malware |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Ajiri, Victor, Butakov, Sergey, Zavarsky, Pavol |
| Conference Name | 2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS) |
| Keywords | android, Blocklists, composabiity, Conferences, Detectors, Human Behavior, Malware, malware detection efficiency, mobile antivirus, mobile security, obfuscated malware, pubcrawl, Resiliency, security, signature repository, static analysis, static analyzer |
| Abstract | Mobile antivirus technologies incorporate static analysis which involves the analysis of programs without its execution. This process relies on pattern matching against a signature repository to identify malware, which can be easily tricked by transformation techniques such as obfuscation. Obfuscation as an evasion technique renders character strings disguised and incomprehensive, to prevent tampering and reengineering, which poses to be a valuable technique malware developers adopt to evade detection. This paper attempts to study the detection efficiency of static analyzers against obfuscated Android malware. This study is the first step in a larger project attempting to improve the efficiency of malware detectors. |
| DOI | 10.1109/BigDataSecurity-HPSC-IDS49724.2020.00049 |
| Citation Key | ajiri_detection_2020 |
Detection Efficiency of Static Analyzers against Obfuscated Android Malware