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Challenges and Solutions for Cybersecurity and Adversarial Machine Learning

By Shafiq Ul Rehman

Product Image: Challenges and Solutions for Cybersecurity and Adversarial Machine Learning

Challenges and Solutions for Cybersecurity and Adversarial Machine Learning

By Shafiq Ul Rehman

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Description
Adversarial machine learning poses a threat to cybersecurity by exploiting vulnerabilities in AI models through manipulated inputs. These attacks can cause systems in healthcare, finance, and autonomous vehicles to make dangerous or misleading decisions. A major challenge lies in detecting these small issues and defending learning models and organizational data without sacrificing performance. Ongoing research and cross-sector collaboration are essential to develop robust, ethical, and secure machine learning systems. Further research may reveal better solutions to converge cyber technology, security, and machine learning tools. Challenges and Solutions for Cybersecurity and Adversarial Machine Learning explores adversarial machine learning and deep learning within cybersecurity. It examines foundational knowledge, highlights vulnerabilities and threats, and proposes cutting-edge solutions to counteract adversarial attacks on AI systems. This book covers topics such as data privacy, federated learning, and threat detection, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and data scientists.
Product details
Binding:
Paperback
Number of Pages:
568
Release Date:
2025-06-06
Publication Date:
2025-06-06
Publisher:
IGI Global
Languages:
Original: English
ISBN13:
9798337322018
GPSR Manufacturer Reference:
[email protected]
Weight:
1054 g
Height:
178 cm
Width:
254 cm
Thickness:
30 cm
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