In today's hyperconnected world, cyber threats are evolving faster than ever before, growing in complexity, stealth, and impact. Traditional forensic techniques, while foundational, are increasingly challenged by the scale and velocity of modern network traffic. This book, AI-Powered Network Forensics: Analyzing Data to Trace Cyber Attacks , is born out of the urgent need to rethink how we detect, analyze, and respond to cyber incidents. By blending the fields of artificial intelligence and digital forensics, this work ...
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In today's hyperconnected world, cyber threats are evolving faster than ever before, growing in complexity, stealth, and impact. Traditional forensic techniques, while foundational, are increasingly challenged by the scale and velocity of modern network traffic. This book, AI-Powered Network Forensics: Analyzing Data to Trace Cyber Attacks , is born out of the urgent need to rethink how we detect, analyze, and respond to cyber incidents. By blending the fields of artificial intelligence and digital forensics, this work explores how machine learning, deep learning, and intelligent data processing can augment the capabilities of investigators, enabling faster and more accurate threat attribution across massive datasets. This book is intended for cybersecurity professionals, digital forensics analysts, researchers, and students seeking to understand how AI can revolutionize the art and science of network forensics. Through real-world examples, algorithmic walkthroughs, and system design considerations, readers will gain practical insights into building AI-driven forensic pipelines - from anomaly detection to attacker profiling. As cyberattacks grow more sophisticated, this book aims to equip you with the tools and concepts needed to stay ahead, leveraging AI not just as a support tool, but as a core component of the forensic process.
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