9783032173669 - guide to ai for cybersecurity: principles, frameworks, and practical implementation (texts in computer science) von ramachandran, muthu (4 Ergebnisse)
- Hardcover
Anbieter: Majestic Books, Hounslow, , Vereinigtes KönigreichMajestic Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 135,29
EUR 7,49 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 4 verfügbar
Zustand: New.
- Hardcover
Anbieter: Revaluation Books, Exeter, , Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 130,61
EUR 17,28 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
Hardcover. Zustand: Brand New. 819 pages. 6.14x1.69x9.21 inches. In Stock.
- Hardcover
Anbieter: moluna, Greven, , Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 98,74
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 89,08
EUR 66,61 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - With cybercrime costs exceeding $10.5 trillion annually and ransomware attacks predicted every two seconds by 2031, traditional signature-based security has reached critical breaking points. Guide to AI for Cybersecurity provides the essential roadmap for h…arnessing artificial intelligence as a force multiplier against sophisticated, AI-powered threats.This comprehensive textbook bridges the gap between artificial intelligence theory and practical cybersecurity applications through 18 chapters organized around an innovative detection, response, prediction, and prevention (DRPP) framework. Drawing from recent high-impact incidents including the 2025 Collins Aerospace cyberattack, the Marks & Spencer ransomware attack, and the Co-op data breach readers progress from foundational concepts to advanced implementations, gaining hands-on experience with production-ready code examples, real-world case studies, and comprehensive deployment guidance for AI-powered security solutions.Topics and features: Introduces the DRPP framework for systematically implementing AI security across the complete security lifecycle Includes complete instructor resources for flexible course adoption PowerPoint slides, laboratory exercises, assessment questions, and implementation projects Provides comprehensive coverage of machine learning (ML) for threat detection, adversarial AI defenses, and automated incident response Integrates ethics, governance, and regulatory compliance (GDPR, CCPA, AI Act) throughout, with dedicated coverage of privacy-preserving techniques Offers detailed guidance on integrating AI capabilities with industry standards while maintaining compliance requirementsThis essential textbook/guide provides comprehensive coverage suitable for graduate students in computer science, cybersecurity, or AI/ML programs, as well as cybersecurity professionals seeking to master AI-powered defense techniques. Software architects building secure AI systems, academic instructors developing AI security courses, and researchers investigating adversarial machine learning also will find the volume invaluable.Muth.
