Visible to the public Malware Classification Using Machine Learning Algorithms

TitleMalware Classification Using Machine Learning Algorithms
Publication TypeConference Paper
Year of Publication2018
AuthorsUdayakumar, N., Saglani, V. J., Cupta, A. V., Subbulakshmi, T.
Conference Name2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI)
KeywordsComputer architecture, Conferences, core computing functions, Correlation, Decision trees, encrypting deleting sensitive data, huge virtual world, Human Behavior, Internet, invasive software, learning (artificial intelligence), machine learning algorithms, malicious programs, malicious software, Malware, malware classification, Malware crisis, Metrics, pattern classification, privacy, pubcrawl, resilience, Resiliency, scripts, stealing deleting sensitive data, Support vector machines
Abstract

Lately, we are facing the Malware crisis due to various types of malware or malicious programs or scripts available in the huge virtual world - the Internet. But, what is malware? Malware can be a malicious software or a program or a script which can be harmful to the user's computer. These malicious programs can perform a variety of functions, including stealing, encrypting or deleting sensitive data, altering or hijacking core computing functions and monitoring users' computer activity without their permission. There are various entry points for these programs and scripts in the user environment, but only one way to remove them is to find them and kick them out of the system which isn't an easy job as these small piece of script or code can be anywhere in the user system. This paper involves the understanding of different types of malware and how we will use Machine Learning to detect these malwares.

URLhttps://ieeexplore.ieee.org/document/8553780
DOI10.1109/ICOEI.2018.8553780
Citation Keyudayakumar_malware_2018