International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
Webpage URL: https://airccse.org/journal/ijnsa.html
A Survey on Malware Detection and Analysis Tools
Sajedul Talukder1 and Zahidur Talukder2, 1Edinboro University, USA and 2University of Texas at Arlington, USA
Abstract
The huge amounts of data and information that need to be analyzed for possible malicious intent are one of the big and significant challenges that the Web faces today. Malicious software, also referred to as malware developed by attackers, is polymorphic and metamorphic in nature which can modify the code as it spreads. In addition, the diversity and volume of their variants severely undermine the effectiveness of traditional defenses that typically use signature-based techniques and are unable to detect malicious executables previously unknown. Malware family variants share typical patterns of behavior that indicate their origin and purpose. The behavioral trends observed either statically or dynamically can be manipulated by using machine learning techniques to identify and classify unknown malware into their established families. This survey paper gives an overview of the malware detection and analysis techniques and tools.
Keywords
Malware, Detection, Analysis, Tools, Machine Learning
Original Source URL: https://aircconline.com/ijnsa/V12N2/12220ijnsa03.pdf
Volume URL: https://airccse.org/journal/jnsa20_current.html
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