Nouveauté
| Titre : | Artificial Intelligence and Cybersecurity |
| Auteurs : | Fisher Natalie, Auteur |
| Type de document : | texte imprimé |
| Editeur : | 3G E-Learning, 2025 |
| ISBN/ISSN/EAN : | 978-1-984694-63-8 |
| Format : | 303 p. / ill. / 25 cm |
| Langues: | Anglais |
| Langues originales: | Anglais |
| Index. décimale : | 004 (informatique en général) |
| Catégories : | |
| Mots-clés: | Artificial Intelligence ; Cybersecurity ; Machine Learning ; Threat Detection ; Intrusion Detection Systems ; Anomaly Detection ; Network Security ; Automated Incident Response ; Malware Analysis ; Predictive Analytics ; Data Security ; Cyber Defense ; Advanced Persistent Threats ; Zero-Day Attacks ; Ethical Issues in AI ; Privacy Protection ; Security Automation ; AI-Based Monitoring ; Risk Management ; Future Trends in Cybersecurity |
| Résumé : | Artificial Intelligence and Cybersecurity offers a comprehensive exploration of how modern artificial intelligence (AI) technologies intersect with the field of cybersecurity in response to rapidly evolving digital threats. Authored by Natalie Fisher and published in 2025, the book examines the full landscape of cybersecurity challenges and demonstrates how AI tools—especially machine learning, pattern recognition, and predictive analytics—can be applied to protect networks, systems, and data from increasingly sophisticated attacks.The book begins by defining core concepts in both AI and cybersecurity, establishing a foundation that is accessible to students, IT professionals, and security practitioners alike. It explains why traditional, rule-based security systems struggle to keep up with the volume and complexity of contemporary threats, such as zero-day exploits, advanced persistent threats (APTs), and automated botnet attacks. AI’s ability to learn from vast datasets enables proactive threat detection and real-time response—shifting the paradigm from reactive defense toward predictive and adaptive security mechanisms.A key part of the text delves into practical applications: AI-powered intrusion detection systems, anomaly detection frameworks, and automated incident response tools. The author illustrates how machine learning models can analyze network behavior, uncover subtle patterns that indicate malicious activities, and trigger defensive actions faster than human operators alone. The book also addresses ethical and governance issues related to AI in cybersecurity, such as privacy concerns, bias in algorithms, and the potential misuse of AI by attackers.Throughout the chapters, Artificial Intelligence and Cybersecurity combines theoretical insights with real-world use cases and case studies to show how organizations can integrate AI into their security strategies effectively. The book concludes with a look toward future trends, including the role of explainable AI, autonomous defense systems, and policy frameworks that can guide responsible AI deployment in cybersecurity environments. |
Exemplaires (2)
| Code-barres | Cote | Support | Localisation | Section | Disponibilité |
|---|---|---|---|---|---|
| 25/162 | 004/2271/1 | Livre | BU Centrale Batna 1 | Deuxième étage : Architecture, sciences et technologies | Disponible |
| 25/163 | 004/2271/2 | Livre | BU Centrale Batna 1 | Deuxième étage : Architecture, sciences et technologies | Disponible |
