Autorentext

Dr. Akshay Mudgal is a visionary Cyber Security Professional, Researcher, and Academician whose unwavering dedication to the field of Cyber Security has established him as a prominent figure in both academia and industry. Renowned for his profound expertise in Network Security, Information Security, Cyber Security, Big Data, Dark Net/Web, and Blockchain, Dr. Mudgal has made substantial contributions to advancing the domain with his remarkable research and modern innovations.

Holding a prestigious Ph.D. in Cyber Security, Dr. Mudgal's academic journey is a testament to his commitment to excellence. In addition to his doctorate, he possesses advanced degrees in Computer Applications (MCA) and Business Administration (MBA - Information System Management), Bachelor of Science in Information Technology (B.Sc. IT) along with a Bachelor of Science in Information Security. His academic foundation is further bolstered by a suite of esteemed professional certifications.

Klappentext

Cybersecurity in the Big Data Era is a fascinating look at the invisible fight going on under our networked lives. In a world where every heartbeat of society is mirrored in digital code, this book shows us how to protect ourselves. This book is more than simply a technical handbook; it's a wake-up call, a roadmap, and a survival aid for anybody who uses digital systems, from business executives and IT professionals to regular people.

Go to the nerve center of modern civilization, where power grids, hospitals, banks, and governments all work together perfectly in the digital world-until one small breach threatens to bring it all crashing down. The story starts by showing how important cybersecurity is in today's IT systems. It shows how our dependence on cloud computing, IoT devices, and worldwide networks has made both new opportunities and new risks. Every server, smartphone, and sensor is a possible target, and a successful attack can have effects that are felt all over the world, hurting economies and putting lives at risk.

The book shows the huge costs of cyberattacks on society and the economy through real-life examples like the Equifax and Colonial Pipeline hacks. Cybercrime is now more profitable than the global drug trade, and by 2025, it is expected to cause more than $10 trillion in damage each year. The fallout isn't just money-related; companies also have to deal with damaged reputations, lost trust, and even threats to their very existence, especially small and medium-sized businesses that don't have strong defenses.

But this isn't only a narrative about danger; it's also a story about strength and new ideas. The book explains how the threat landscape is changing quickly, with enemies using AI-generated phishing, deepfakes, and zero-day attacks in very advanced ways. But it also shows how smart automation, proactive security structures, and a human-in-the-loop approach can make things safer and more trustworthy.

Cybersecurity in the Big Data Era delves deeper than the headlines. It gives a more detailed look at the regulatory pressures, skills gaps, and operational problems that businesses have to deal with. It says that cybersecurity is not an obstacle to advancement but a driver of digital innovation, allowing for secure APIs, privacy-by-design, and trustworthy digital identities that will drive the next generation of technical discoveries.

This book turns cybersecurity from a technical afterthought into a strategic must-do by using clear explanations, interesting tales, and useful tips. No matter if you're an experienced professional or just someone who wants to learn more, you'll leave with a better awareness of the risks and the skills to confidently navigate the digital world.

Get ready to experience the digital world in a whole new way: as weak, strong, and full of potential. Cybersecurity in the Big Data Era is the most important book you can read to stay safe and do well in the era of information.

Inhalt

About the Author. Author's Vision. Foreword. 1. Introduction to Cybersecurity in the Big Data Era. 2. Foundations of Intrusion Detection Systems (IDS). 3. Honeypot Systems: Deception for Defense. 4. Big Data Technologies for Security Analytics. 5. Machine Learning for Intrusion Detection. 6. Building the Hybrid Honeypot-Based ML-Driven IDS Architecture. 7. Dataset Collection, Preprocessing & Labeling. 8. Model Design, Training & Evaluation. 9. Deployment of the Hybrid System in Real-World Environments Depiction. 10. Case Studies, Simulated Attacks, Results and Analysis. 11. Ethical, Legal & Privacy Concerns. 12. Future Trends and Research Directions.