£178.60

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£179 today · previous high £179 · all-time low £155

Information Science Reference Adversarial Machine Learning & Cybersecurity Challenges

Amazon

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£178.60 £153.08 £158.65 £164.22 £169.78 £175.35 £180.92 27 July 2026 12 August 2026 28 August 2026 13 September 2026 29 September 2026
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Description

Adversarial machine learning represents a critical threat to cybersecurity systems, exploiting vulnerabilities in AI models through manipulated inputs that can cause dangerous or misleading decisions across healthcare, finance, and autonomous vehicles. This comprehensive guide addresses the fundamental challenge of detecting adversarial attacks and defending machine learning models while maintaining organisational data security without sacrificing system performance. The book explores how small perturbations can compromise AI integrity and examines cross-sector collaboration strategies essential for developing robust, ethical, and secure machine learning systems. Ideal for security professionals, machine learning engineers, and IT leaders seeking to understand emerging threats and implement effective defences against adversarial attacks in production environments.

Key Features

Addresses adversarial machine learning threats that exploit vulnerabilities in AI models through manipulated inputs and attack vectors.

Examines real-world implications for critical sectors including healthcare systems, financial institutions, and autonomous vehicle safety.

Explores detection methods and defence strategies to protect machine learning models from adversarial attacks whilst maintaining system performance.

Discusses the importance of cross-sector collaboration and ongoing research for developing secure, ethical AI systems.

Provides insights into converging cybersecurity technology with machine learning to protect organisational data and model integrity.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
06 June 2025
Listed Since
28 May 2025

Barcode

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