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This paper explores the application of genetic algorithms to a real-life issue, specifically malware. Malware, or "Malicious" software such as viruses, worms, Trojans, denial-of-service tools, etc., is becoming an increasingly major issue. As more and more people use the Internet for services such as banking or bill-paying and companies becoming increasingly dependent on Internet communication, the damage that can be done by malware increases significantly. At the same time, malware is becoming increasingly sophisticated, making it both more damaging (compare modern malware that can record a user's every keystroke to early viruses that did little more than replicate themselves uncontrollably) and more difficult to detect (most modern malware is deliberately designed to avoid detection).
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