Cybernetic Shield: Securing the Future of Machine Intelligence explores the critical intersection between cybersecurity and the rapid advancements in artificial intelligence. This book addresses the growing need for robust security measures in AI-driven systems by presenting cutting-edge strategies and frameworks that ensure the integrity, trust, and resilience of machine intelligence. It delves into a wide array of emerging cybersecurity challenges-from securing AI-integrated learning platforms in digital education to safeguarding blockchain-based solutions and tackling vulnerabilities in IoT networks. The book offers practical insights into protecting against cyber threats that threaten the changing digital landscape, guaranteeing a future where intelligent technologies can be safely harnessed for innovation and advancement. It does this by drawing on both theoretical analysis and real-world case studies.
This book offers an in-depth exploration of the latest cybersecurity techniques tailored for AI applications. The chapters cover a range of topics, from securing machine learning platforms and mitigating privacy risks in AI-driven healthcare to implementing decentralized blockchain systems and safeguarding critical systems from AI-driven vulnerabilities. Readers will benefit from practical solutions to pressing cybersecurity challenges, expert insights on governance frameworks, and real-world examples of how emerging technologies like IoT, AI, and blockchain are reshaping the future of cybersecurity. The book serves as an essential resource for anyone looking to stay ahead of the curve in the rapidly evolving digital landscape.
Cybernetic Shield: Securing the Future of Machine Intelligence is specifically designed for professionals, researchers, and students in the fields of cybersecurity, AI, and digital technologies. It caters to individuals involved in securing AI systems, blockchain development, and digital infrastructures across various industries, including healthcare, finance, and education. The book is also highly relevant to policymakers, legal experts, and technology leaders who are seeking guidance on creating frameworks to protect the future of machine intelligence. With its comprehensive approach, it appeals to anyone interested in understanding the critical role of cybersecurity in the age of AI and machine learning.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Professional Reference
Illustrationen
45 s/w Zeichnungen, 6 s/w Photographien bzw. Rasterbilder, 51 s/w Abbildungen, 19 s/w Tabellen
19 Tables, black and white; 45 Line drawings, black and white; 6 Halftones, black and white; 51 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Gewicht
ISBN-13
978-1-032-93643-7 (9781032936437)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Arun Kumar Singh is a Professor and Deputy Head of the Department of Computer Science and Engineering at Greater Noida Institute of Technology (GNIOT), India. He has completed specialized training in Intellectual Property and the Patent Cooperation Treaty (PCT) through the World Intellectual Property Organization (WIPO) Academy, enhancing his understanding of legal aspects related to innovation protection. Dr. Singh's diverse career spans positions at multiple institutions including the University of Allahabad, MNNIT, GL Bajaj Institute of Technology and Management, and the Institute of Engineering and Rural Technology, where he has served in various leadership roles. A prolific researcher, Dr. Singh has published in various SCI journals and Scopus-indexed international conferences, authored textbooks and chapters, secured patents and several grants, and worked on projects funded by CSIR and ISEA. His expertise spans cybersecurity, cryptography, machine learning, and computer forensics. Additionally, he is AWS certified and an expert in NBA and NAAC accreditation processes, with a focus on outcome-based education.
Prof. (Dr.) Sandeep Saxena is the Head of Department (HOD) for AIML & AIDS and a Professor at JIMS-EMTC, Greater Noida, India. He earned a Ph.D. in Computer Science and Engineering from NIT Durgapur, West Bengal, and has over 16 years of teaching and research experience. Dr. Saxena specializes in Blockchain Technology and Cloud Computing, particularly focusing on Security and Privacy. Dr. Saxena has contributed to over 20 international conferences, as a Keynote Speaker, Organizing Secretary, Organizing Chair, and Session Chair. He's authored four technical books, published over 50 research papers in top international journals and conferences, and holds three patents with more than 10 additional patents published. As a Senior Member of IEEE and IAASSE, and a Lifetime Member of CSI and CRSI, he is actively involved in professional societies. Dr. Saxena is involved in research and development, university syllabus design, and guiding student innovation and incubation projects. Additionally, he has been a reviewer of leading journals and conferences, maintaining the integrity of academic work, and has contributed to accreditation bodies like NAAC and NBA, helping to improve the educational landscape.
Prof. A. K. Haghi is a retired professor who has written, co-written, edited, or co-edited more than 1000 publications, including books, book chapters, and papers in refereed journals. He holds a BSc in urban and environmental engineering from the University of North Carolina (USA) and holds two MSc degrees, one in mechanical engineering from North Carolina State University (USA) and another one in applied mechanics, acoustics, and materials from the Universite de Technologie de Compiegne (France). Prof. Haghi was also awarded a PhD in engineering sciences at Universite de Franche-Comte (France). His extensive educational background and supervisory roles underscore his expertise and contributions to the field of engineering sciences. He is an appointed Honorary Research Associate (HRA) at the University of Coimbra, Portugal, and a regular reviewer of leading international journals.
Herausgeber*in
Prof., Dept. of Comp. Sci. & Eng., GNIOT
Prof., Dept. of Comp. Sci. & Eng., GNIOT
Research Associate, Univ. of Coimbra
1 Cyber Defense Strategies for Ensuring Electoral Trust and Integrity. 2. Cyber Barriers: Leveraging IoT-Driven Security Systems for Enhanced Wildlife Protection. 3. Ciphering Authenticity: Unveiling Signature Forgery with CNN. 4. AI Governance and Cybersecurity: A Legal Framework for Safeguarding the Future of Machine Intelligence. 5. Securing AI-Integrated Learning Platform: Cyber Threats in the Age of Digital Education. 6. Blockchain-Decentralized approach for Crowdfunding using ECDSA with P-256 and SHA-256 algorithm. 7. Cyberbullying Text Classification Using NLP - Algorithm-Based Techniques. 8. Enhancing Election Integrity with Cybersecurity Solutions. 9. Mitigating Privacy and Security Risks of Federated Learning in Smart Healthcare: Analysis. 10. Privacy-Preserving Federated Transfer Learning for Brain Tumor Multi-Classification in AI-Driven Healthcare. 11. Futuristic Health Care Management System Using AI. 12. Open-Access Datasets for Brain-Computer Interfaces Research. 13. Navigating the Risks: Cybersecurity Challenges Stemming from AI Breaches in Critical Systems. 14. Machine Learning Based Model for Detecting Cyber Attack Vulnerabilities. 15. Exploring Big Tech Vulnerabilities: Transparent Blockchain Harvesting. 16. Comprehensive Guide to Blockchain Technology: Ecosystems, Implementation, Governance, and Innovations. 17. Cloud Based Business Application with Automated Resource Scaling and Optimized Job Scheduling. 18. Addressing Data Security and Privacy Challenges: A Critical Analysis of Convolutional Neural Networks (CNN) Applications. 19. Cybernetic Shield and IoT-Based Vibration Fencing for Wildlife Protection. 20. Enhanced Object Detection in Underwater Imaging using Deep Learning Method. 21. Explaining and Adapting: Self-Healed AI Security Systems for Future Cybersecurity.
