Implementasi Teknologi AI Dalam Deteksi dan Pencegahan Serangan Malware pada Jaringan Komputer Perusahaan

Abstract

This research aims to explore in depth the implementation of AI technology in the context of detecting and preventing malware attacks on corporate computer networks. Through a comprehensive literature review and in-depth analysis, this research outlines various AI techniques that can be applied to overcome malware threats, including machine learning, deep learning, and malware behavior analysis. We will highlight the latest research and relevant case studies for each technique, as well as analyze their strengths and limitations in detecting and preventing malware attacks. In addition, this research will also discuss the significant challenges faced in implementing AI technology for malware detection, such as the availability of quality training data, rapid malware adaptation, and complexity and resource limitations. We will explore strategies and approaches that can be implemented to overcome these challenges. Finally, this research will explore the opportunities offered by AI technology in improving corporate network security against malware attacks. We will discuss how integrating AI technology into a holistic network security strategy can provide more accurate and effective malware detection, automated response to attacks, and deeper malware analysis and forensics.