Md. Enamul Karim

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Malicious programs, such as viruses and worms, are frequently related to previous programs through evolutionary relationships. Discovering those relationships and constructing a phylogeny model is expected to be helpful for analyzing new malware and for establishing a principled naming scheme. Matching permutations of code may help build better models in(More)
Programmers obfuscate their code to defeat manual or automated analysis. Obfuscations are often used to hide malicious behavior. In particular, malicious programs employ obfuscations of stack-based instructions, such as call and return instructions, to prevent an analyzer from determining which system functions it calls. Instead of using these instructions(More)
Using plant database we investigate the distribution of different tuples of small length for TATA and TATA-less promoters. Results show that in the neighborhood of TATA patterns some of the tuples demonstrate discriminating distribution for TATA and TATA-less promoters. Based on this observation we perform probabilistic learning to recognize TATA promoters(More)
In this paper we present a random shuffling scheme to apply with adaptive sorting algorithms. Adaptive sorting algorithms utilize the presortedness present in a given sequence. We have probabilistically increased the amount of presortedness present in a sequence by using a random shuffling technique that requires little computation. Theoretical analysis(More)
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