ADVERSARIALuscator: An Adversarial DRL (AI) based advanced Metamorphic Malware Swarm Generator
Presentation of a research paper in the 'International Joint Conference on Neural Networks, a Core A-rated Neural Network conference.
The paper covers the research and development of a system, named as ADSARIALuscator.
Objective:
Generation of a Swarm of Advanced metamorphic malware and ransomware, by using obfuscation.
Metamorphic malware could alter its internal structure with every attack.
If such malware could intrude even into any of the IoT networks, then even if the original malware instance gets detected, by that time it can still infect the entire network with its different mutations.
We present ADVERSARIALuscator, a novel system that:
• uses specialized Adversarial DRL to obfuscate malware at the opcode level and create multiple metamorphic instances of the same.
• It is the first-ever system that adopts the MDP/RL-based approach to convert and find a solution to the problem of creating individual obfuscations at the opcode level.
• This is important as it is the lowest level at which functionality could be preserved to mimic an actual attack effectively.
• is also the first-ever system to use efficient continuous action control capable DRL agents like the
PPO in the area of cybersecurity.
Hence ADVERSARIALuscator could be used to:
• generate data representative of a swarm of very potent and coordinated AI-based
metamorphic malware attack.
• The so generated obfuscations could be used to bolster the defenses of a malware detection system against an actual AI-based metamorphic and ransomware swarm attack.