Madhu K. Shankarapani

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One of the major problems concerning information assurance is malicious code. To evade detection, malware has also been encrypted or obfuscated to produce variants that continue to plague properly defended and patched networks with zero day exploits. With malware and malware authors using obfuscation techniques to generate automated polymorphic and(More)
In this paper we present a method of functionally classifying malicious code that might lead to automated attacks and intrusions using kernel machines. We study the performance of kernel methods in the context of robustness and generalization capabilities of malware classification.
Malware, in essence, is an infiltration to one’s computer system. Malware is created to wreak havoc once it gets in through weakness in a computer’s barricade. Anti-virus companies and operating system companies are working to patch weakness in systems and to detect infiltrators. However, with the advance of fragmentation, detection might even prove to be(More)
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