• VENKATESWARANAIDU KOLLURI

This paper presents advanced malware analysis and detection methods enabled by artificial intelligence (AI). Today, Malware still remains one of the most dangerous threats to cybersecurity, while attackers obtain new methods of escaping traditional detection mechanisms. Employing AI techniques such as Machine Learning, Deep Learning and Natural Language Processing, it is vital to reflect on new strategies for revealing malware, enhance detection accuracy and diminish the role it plays in cyber campaigns [1]. This will focus to further step-up cybersecurity deployment to prevent the rise of newer cybersecurity challenges. The paper examines different AI-based methods explicitly, such as supervised and unsupervised learning algorithms, reinforcement learning techniques, and deep neural networks, with in depth analysis of their efficiency in malware detection and analysis in different environments [1]. Additionally, it examines the integration of AI-enabled malware analysis platforms with existing cybersecurity architectures which also reveal some of the possible advantages and constraints for such deployment. Furthermore, cybersecurity ethics and legality aspects of AI implementation are discussed which stress the need for responsible AI governance and transparency as tools to maintain the trust in AI-driven malware detection systems.

Malware analysis, Artificial intelligence, Machine learning, Deep learning, Natural language processing, Cybersecurity, Cyber-attacks, Artificial Intelligence, Cybersecurity, ,Automated Systems, Machine Learning

"CUTTING-EDGE INSIGHTS INTO UNMASKING MALWARE: AI-POWERED ANALYSIS AND DETECTION TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 2, page no.550-554, February-2017, Available :http://www.jetir.org/papers/JETIR1702087.pdf

"CUTTING-EDGE INSIGHTS INTO UNMASKING MALWARE: AI-POWERED ANALYSIS AND DETECTION TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 2, page no. pp550-554, February-2017, Available at : http://www.jetir.org/papers/JETIR1702087.pdf