Abstract

Artificial intelligence (AI) is an effective technology used for upgrading the security posture against a variety of security challenges and cyber-attacks that cyber security teams may use. Malware is a software which aims to access a device without the explicit permission of its owner. Forensics investigations report that many organizations have encountered unusual records, collected by their antiviral security monitoring systems. Most of their arrangements skeptically pass a large amount of diplomatic data through various unethical strategies that make malware identification tougher. However, these procedures have varied limitations that call for an unused inquiry about the track. This study explores the complex relationship between malware detection and AI [1]. This paper provides insights into performance evaluation metrics and discusses several research issues that impede the effectiveness of existing techniques. The study also provides recommendations for future research directions and is a valuable resource for researchers and practitioners working in the field of malware detection.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.