Cybercrime and Pattern Analysis Using Gen AI
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Narrado por:
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Virtual Voice
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De:
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Ajit Singh
Este título utiliza narración de voz virtual
Voz Virtual es una narración generada por computadora para audiolibros..
Philosophy
The core philosophy of this book is that cybersecurity must evolve from a reactive posture to a proactive and intelligent one. Traditional security measures are failing because they are designed to recognize known threats. Modern adversaries, however, create unknown threats. This book champions the use of Generative AI as the key to flipping this paradigm. By learning the underlying patterns of "normal" and "malicious" activities, Generative AI models can not only detect novel attacks but also anticipate them, generate realistic training data for other defense systems, and automate complex security analysis. Our philosophy is rooted in "learning by doing," prioritizing practical implementation over abstract theory.
Key Features
1. Globally Relevant: The curriculum is designed to be compatible with B.Tech/M.Tech Computer Science programs at universities worldwide.
2. Beginner to Advanced: The content is structured to be accessible for students new to AI or cybersecurity while also providing depth and advanced topics for postgraduate students and professionals.
3. Comprehensive Coverage: Includes detailed discussions on model design, architecture, implementation, deployment, and future scope for all major techniques.
4. Complete End-to-End Project: Features a full, working capstone project with explained code, enabling students to build a portfolio-worthy application.
5. Ethical Focus: A dedicated chapter on the ethical, legal, and responsible use of AI in cybersecurity, a critical component of modern engineering education.
To Whom This Book Is For
1. B.Tech and M.Tech Computer Science/IT Students: As a core or elective textbook for courses on Cybersecurity, Artificial Intelligence, Machine Learning, or a specialized combination thereof.
2. Cybersecurity Analysts and Professionals: Who wish to upgrade their skills and learn how to integrate advanced AI techniques into their security operations.
3. AI/ML Engineers and Data Scientists: Who are interested in applying their expertise to the challenging and high-impact domain of cybersecurity.
4. Academic Researchers: As a foundational text for exploring new frontiers in AI-driven security.
5. Self-Learners and Enthusiasts: Anyone with a foundational knowledge of programming and an interest in the future of digital defense.
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