![]() ![]() We showed how the code segments correlate at these levels for studied samples. Specifically, we proposed a deep inspection approach for multi-level profiling of crypto-ransomware, which captures the distinct features at Dynamic link library, function call, and assembly levels. In this work, we developed an AI-powered hybrid approach overcoming the recent challenges to detect ransomware. Numerous research of ransomware with AI techniques often lack the behavioral analysis and its correlation mapping. Various static and dynamic analysis techniques exist, but these methods become less efficient as the malware writers continuously trick the defenders. Mainly, small businesses, healthcare, education, and government sectors have been under continuous attacks by these adversaries. Crypto-ransomware is the most prevalent form of modern malware, has affected various industries, demanding a significant amount of ransom. ![]()
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