Malware Recognition and Pattern Classification Using NLP

  • Roopashree L R, Dr.M. Sreedevi


Malware or malicious software is a general term that refers different or undesirable software. Malware can be categorized according to its purpose into different categories. Computer viruses, ransom ware, spyware, worms, adware and Trojan horses are among the most common types of malware. Malware can be used to disrupt computer activities, to collect sensitive information or to access a private computer device. In stealth mode for malware designed to steal information about computer users or spy for a long period of time without their knowledge, for a long time. Growing malware program is categorically categorized and distinct from other malicious programs with malware and different types of malware programs in every way. Classification is also essential for the development and execution of the appropriate software patch to close the vulnerability of the program. We suggest the identification of URL malware based on the processing of natural language and measure the survey for which malware is most impacted. The HTTP URL is like one of the text documents that can be classified by the processing of natural language. Then we use n gram technique for detecting the network flow for malware on URL. Then, to determine the malware detection survey based on Hidden Markov Model, a heuristic malware analysis technique. The survey covers significant field literatures and concludes that HMM is an efficient and reliable technique for detecting and classifying metamorphic malware.

How to Cite
Roopashree L R, Dr.M. Sreedevi. (2020). Malware Recognition and Pattern Classification Using NLP. International Journal of Advanced Science and Technology, 29(6s), 217 - 223. Retrieved from