Isbn: 9786208445133 - leveraging artificial intelligence and machine learning: for predictive threat hunting in cybersecurity (10 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condición: Neu. LEVERAGING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | FOR PREDICTIVE THREAT HUNTING IN CYBERSECURITY | Kanthavel R (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208445133 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As cybersecurity threats continue to evolve in sophistication, velocity, and impact, the conventional reactive security approaches cannot keep up with them. In these cases, cyber attackers have employed more sophisticated strategies such as polymorphic malware, fileless attacks, and living-off-the-land techniques that do not depend on traditional detection methods. Anticipating this, predictive risk looking (more notably using artificial intelligence (AI) and machine learning) has emerged as a key technology in today's cybersecurity strategies. Predictive risk finding allows security teams to proactively detect hidden risks, spot anomalies, and anticipate adversary behaviours before it results in a breach or device compromise. AI/ML approaches leverage behavioural analytics, large-scale telemetry data, and real-time learning to uncover overlooked patterns often missed by human analysts or rule-based architectures. In this article, we provide an exclusive overview of today's cutting-edge AI and ML applications in predictive risk looking. We focus on core technologies, device architectures, algorithmic models, and industry specific implementations.…

Condición: New. Print on Demand.

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As cybersecurity threats continue to evolve in sophistication, velocity, and impact, the conventional reactive security approaches cannot keep up with them. In these cases, cyber attackers have employed more sophisticated strategies such as polymorphic malware, fileless attacks, and living-off-the-land techniques that do not depend on traditional detection methods. Anticipating this, predictive risk looking (more notably using artificial intelligence (AI) and machine learning) has emerged as a key technology in today's cybersecurity strategies. Predictive risk finding allows security teams to proactively detect hidden risks, spot anomalies, and anticipate adversary behaviours before it results in a breach or device compromise. AI/ML approaches leverage behavioural analytics, large-scale telemetry data, and real-time learning to uncover overlooked patterns often missed by human analysts or rule-based architectures. In this article, we provide an exclusive overview of today's cutting-edge AI and ML applications in predictive risk looking. We focus on core technologies, device architectures, algorithmic models, and industry specific implementations.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…