Advanced AI Techniques for Cybersecurity: Concepts, Architectures, And Emerging Trends
This book discusses the impact of more sophisticated artificial intelligence methods and practices that are changing the current state of cybersecurity, allowing proactive, adaptive and automated defense. It offers the basics of AI and machine learning, changing nature of threat and how data analytics is used to detect malicious trends. Basic chapters describe the intrusion detective, malware analysis, and predictive intelligence supervised, unsupervised, deep, and reinforcement learning frameworks. The article considers the use of AI in cloud, IoT, and SOC activities with a focus on automated response and threat hunting. Specialized sections focus on adversarial learning of machines, machine resiliency, explainability, privatization aware methods, and governance. Future directions are discussed as the emerging trends of graph neural networks, edge AI, federated learning, and autonomous cyber defense. The book in general gives a systematic guide to researchers and practitioners on how to develop resilient smart security systems.
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Rahul Karne, Sai Teja Erukude, Suhasnadh Reddy Veluru, Viswa Chaitanya Marella
Rahul Karne is a cybersecurity leader and digital forensics expert, serving as Security Analyst at American Airlines and advisor to startups. A CISSP-certified professional, he specializes in threat detection, cloud security, and AI-driven defense, with publications and patents focused on practical enterprise protection.
Sai Teja Erukude is a Data Scientist at Koch Ag & Energy Solutions. He holds an MS in Computer Science from Kansas State University and has 5+ years of experience, 17+ publications, and a patent pending, focusing on responsible AI, MLOps, and scalable analytics.
Suhasnadh Veluru is an ERP System Administrator with a Master’s in Data Analytics from Kansas State University. He specializes in data engineering, reporting automation, and enterprise system integration for analytics-driven operations
Viswa Chaitanya Marella is a Database Administrator at Centralia College specializing in SQL Server, Power BI, and ERP systems, building data warehouses and automated pipelines to strengthen reporting and governance.
