THE EVOLUTION AND IMPACT OF MACHINE LEARNING IN MODERN APPLICATION SECURITY
Keywords:
Application Security, Machine Learning, Cyber Threat Detection, Federated Learning, Quantum-Ready InfrastructureAbstract
Machine learning has emerged as a transformative force in application security, revolutionizing how organizations detect, prevent, and respond to cyber threats. This comprehensive article examines the implementation of ML-based security solutions across enterprise environments, exploring their impact on threat detection, behavioral analytics, and automated security testing. The article investigates current challenges in data quality, resource optimization, and adversarial resistance while examining future directions in explainable AI, federated learning, and quantum-ready security infrastructure. The article demonstrates significant improvements in security operations efficiency, threat detection capabilities, and incident response times, while highlighting the importance of addressing implementation challenges for optimal security outcomes.
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