| Title | A Malware Variant Resistant To Traditional Analysis Techniques |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Murali, Ritwik, Ravi, Akash, Agarwal, Harshit |
| Conference Name | 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE) |
| Keywords | Analysis Aware Malware, Human Behavior, Malware, malware analysis, Predictive Metrics, privacy, Proactive Malware Research, pubcrawl, Resiliency, Split Personality Malware |
| Abstract | In today's world, the word malware is synonymous with mysterious programs that spread havoc and sow destruction upon the computing system it infects. These malware are analyzed and understood by malware analysts who reverse engineer the program in an effort to understand it and provide appropriate identifications or signatures that enable anti-malware programs to effectively combat and resolve threats. Malware authors develop ways to circumvent or prevent this analysis of their code thus rendering preventive measures ineffective. This paper discusses existing analysis subverting techniques and how they are overcome by modern analysis techniques. Further, this paper proposes a new method to resist traditional malware analysis techniques by creating a split-personality malware variant that uses a technique known as shadow attack. The proposal is validated by creating a malware dropper and testing this dropper in controlled laboratory conditions as a part of the concept of proactive defense. |
| DOI | 10.1109/ic-ETITE47903.2020.264 |
| Citation Key | murali_malware_2020 |
A Malware Variant Resistant To Traditional Analysis Techniques