AI-Based Solutions for Malware Detection and Prevention
Tukkappa K. Gundoor, Sridevi, Rajeev Mulimani · Advances in computational intelligence and robotics book series · 2024
One of the biggest cybersecurity threats worldwide is malware. As cyber-threats evolve, traditional methods become less effective. Leveraging Artificial Intelligence (AI) can improve detection and prevention. Modern malware bypasses signature-based detection, necessitating adaptive AI solutions. Techniques like supervised, unsupervised, and reinforcement learning recognize malware patterns in large datasets. Neural networks outperform regular methods by learning complex features. Integrating AI with network behavior analysis, anomaly detection, and threat intelligence creates robust systems. AI is crucial for stopping zero-day malware and predicting threats. Ethical considerations, such as data privacy and algorithm bias, highlight the need for responsible AI use. Real-world applications by top cybersecurity companies show AI's effectiveness. The future looks promising with AI combined with edge computing, blockchain, and quantum computing, enhancing cybersecurity resilience.