Cyber Resilience: Federated Learning and Adaptive AI Through BCI and Neurotechnological Synergy
Editat de Swati Sah, Aditya Dayal Tyagi, Rejwan Bin Sulaiman, Pranjali Gajbhiyeen Limba Engleză Hardback – 11 feb 2027
The book examines how Federated Learning enables collaborative AI model development without sharing sensitive data, while Adaptive AI continuously learns from evolving environments to detect, predict, and respond to emerging cyber threats. It also highlights the growing role of BCIs and neurotechnology in enhancing authentication, decision-making, cognitive cybersecurity, and human–AI collaboration.
Covering both theoretical foundations and practical applications, the book discusses topics such as explainable AI, adversarial learning, secure edge and cloud computing, blockchain-enabled trust, zero-trust security, and ethical AI. Through real-world case studies from healthcare, finance, smart cities, defense, and Industry 5.0, it demonstrates how these technologies can enhance cyber resilience. Designed for researchers, practitioners, students, and policymakers, this book provides valuable insights into developing intelligent, trustworthy, and future-ready cybersecurity solutions.
Preț: 708.35 lei
Preț vechi: 1009.09 lei
-30% Precomandă
Puncte Express: 1063
Carte nepublicată încă
Livrare prin curier în România Precomanda se expediază când titlul devine disponibil.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Doresc să fiu notificat când acest titlu va fi disponibil:
Se trimite...
Specificații
ISBN-13: 9781041166757
ISBN-10: 1041166753
Pagini: 360
Ilustrații: 82
Dimensiuni: 178 x 254 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 1041166753
Pagini: 360
Ilustrații: 82
Dimensiuni: 178 x 254 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Public țintă
Academic, Postgraduate, and Professional ReferenceCuprins
Chapter 1: Introduction: The Convergence of Federated Learning, BCI, and Cyber Resilience. Chapter 2: Federated Learning Foundations for Secure and Private AI. Chapter 3: Cyber Threat Models and Attack Surfaces in Federated Learning System. Chapter 4: Brain-Computer Interfaces (BCIs): Opportunities and Security Challenges. Chapter 5: Neuro-Adaptive Defense Mechanisms for Federated Learning. Chapter 6: Privacy-Preserving Learning with Cognitive Feedback Loops. Chapter 7: Resilient Architectures for Federated Learning: Design Patterns and Recovery Models. Chapter 8: Blockchain and Distributed Ledger Technologies in Resilient FL System. Chapter 9: Energy-Conscious and Secure Edge Devices for Brain-AI Integration. Chapter 10: Explainable AI in Neuro-Federated Learning Environments. Chapter 11: Case Study: Cyber-Resilient Neuro-AI in Healthcare Systems. Chapter 12: Case Study: Federated Brain-AI Systems in Smart Industry Applications. Chapter 13: Case Study: Federated Brain-AI Systems in Smart Industry Applications. Chapter 14: Legal, Ethical, and Regulatory Challenges in Neuro-Federated AI. Chapter 15: Simulating Attacks and Recovery in Federated Neuro-AI Systems. Chapter 16: Future of Secure Neuro-Symbolic Federated Intelligence. Chapter 17: Conclusion: Building Secure, Resilient.
Notă biografică
Swati Sah
Dr. Swati Sah is a Professor at Sharda University, India, with more than 12 years of experience in higher education, research, academic leadership, and international collaborations. She has built a distinguished academic career through her contributions to teaching, research, curriculum development, and institutional administration.
Prior to joining Sharda University, Dr. Sah served as a faculty member at Amity University, Uzbekistan. In May 2018, she was appointed as the Head of the Department of Computer Science at Patan College for Professional Studies (PCPS), Nepal, an institution affiliated with the University of Bedfordshire, United Kingdom. During her tenure, she played a pivotal role in strengthening academic programs, promoting research activities, and fostering industry–academia collaboration.
Dr. Sah holds a Master of Computer Applications (MCA) from Dr. A.P.J. Abdul Kalam Technical University (formerly Uttar Pradesh Technical University), Lucknow, India, and an M.Sc. from Birmingham City University, United Kingdom. Throughout her academic journey, she has remained actively involved in professional societies, research collaborations, curriculum design, mentoring undergraduate and postgraduate students, and supervising research projects.
Her research interests encompass Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Data Analytics, Intelligent Systems, and AI-driven Decision Support Systems. She has authored and edited scholarly books, published research articles in reputed journals and conference proceedings, and presented her work at numerous national and international conferences. She also serves as a reviewer, editor, and external examiner for academic journals, conferences, and doctoral research.
Dr. Sah's current research focuses on developing intelligent cybersecurity frameworks that leverage Artificial Intelligence and Machine Learning for cyber threat detection, risk assessment, anomaly detection, and automated incident response. She is equally passionate about interdisciplinary research that applies emerging technologies to healthcare, education, agriculture, and smart digital ecosystems.
A strong advocate of innovation and lifelong learning, Dr. Sah actively mentors students and researchers, encourages collaborative research, and promotes the responsible and ethical adoption of Artificial Intelligence. Her vision is to bridge the gap between cutting-edge research and practical applications by developing intelligent, secure, and sustainable technology solutions that create meaningful societal impact.
Research Interests
Aditya Dayal Tyagi
Aditya Dayal Tyagi is a passionate academician, mentor, and researcher. He is specialist in Data Structure, Algorithm Design and Analysis, and Data Base Technologies. He has 20+ years of teaching experience in MCA/B.Tech (CSE/IT) students. He completed his MCA from Dewan Institute of Management Technology Meerut, Uttar Pradesh Technical University (UPTU) – Lucknow and earned his M. TECH in Computer Science and Engineering from GBTU-Lucknow (Previously known as Uttar Pradesh Technical University (UPTU) – Lucknow). He is pursuing his Ph.D from JayPee Institute of Information Technology (Deemed to be University), Noida. His research areas are Information Diffusion, Social Network Analysis, Sentiments Analysis, Signcyption Approach, Deep Learning, and algorithm analysis. He is authored of a book titled "AI-Powered Pricing: Transforming Business with Intelligent Pricing Models." He has one patent and published and presented many research papers in International Journals, International Conferences and National Conferences of repute
Rejwan Bin Sulaiman
Dr. Rejwan Bin Sulaiman is currently serving as a Lecturer in Cyber Security at the University of Law, United Kingdom. He earned his Ph.D. in Artificial Intelligence and Cybersecurity from the University of Bedfordshire, where his doctoral research focused on federated learning-based approaches for secure and privacy-preserving financial AI systems. He has held academic positions at several institutions, including Northumbria University and Arden University.
Dr. Sulaiman’s research spans Cybersecurity, Artificial Intelligence, Computer Vision, and Machine Learning, with particular interest in developing decentralized AI models that enhance data security and user privacy. His work has been published in leading venues such as IEEE, Springer, and CRC Press, contributing to the advancement of secure machine learning frameworks in distributed environments.
He is a Certified Ethical Hacker (CEH) and the founder of STEMResearch.Ai, an initiative that supports and mentors early-career researchers in STEM fields. He is also a Fellow of the Higher Education Academy (FHEA) and has received multiple awards recognizing his innovative teaching practices and dedication to academic excellence.
Pranjali Gajbhiye
Dr. Pranjali Gajbhiye is currently working as a Neuroscientist at Woxsen University, Hyderabad, India, with a strong academic and industry background in biomedical signal processing. With two years of hands-on experience in the BCI-based healthcare industry, she specializes in EEG and fNIRS signal processing using wearable sensing technologies. She holds a PhD in Biomedical Signal Processing (ECE) from BITS Pilani, an M.Tech in Communication System Engineering from VNIT Nagpur, and a B.Tech in ECE from Nagpur University. Her research interests include biomedical signal processing, image and video processing, medical image analysis, and IoT applications in healthcare. She has authored 12+ research articles, contributed to multiple book chapters, and presented at numerous international conferences. She holds 5 patents (published), and serves as a book editor. Her work is published in Q1 journals, including IEEE Transactions on Instrumentation and Measurement. She also contributes academically as a Review Editor for the Q1 journal Frontiers in Physiology (Impact Factor 4.13)
Dr. Swati Sah is a Professor at Sharda University, India, with more than 12 years of experience in higher education, research, academic leadership, and international collaborations. She has built a distinguished academic career through her contributions to teaching, research, curriculum development, and institutional administration.
Prior to joining Sharda University, Dr. Sah served as a faculty member at Amity University, Uzbekistan. In May 2018, she was appointed as the Head of the Department of Computer Science at Patan College for Professional Studies (PCPS), Nepal, an institution affiliated with the University of Bedfordshire, United Kingdom. During her tenure, she played a pivotal role in strengthening academic programs, promoting research activities, and fostering industry–academia collaboration.
Dr. Sah holds a Master of Computer Applications (MCA) from Dr. A.P.J. Abdul Kalam Technical University (formerly Uttar Pradesh Technical University), Lucknow, India, and an M.Sc. from Birmingham City University, United Kingdom. Throughout her academic journey, she has remained actively involved in professional societies, research collaborations, curriculum design, mentoring undergraduate and postgraduate students, and supervising research projects.
Her research interests encompass Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Data Analytics, Intelligent Systems, and AI-driven Decision Support Systems. She has authored and edited scholarly books, published research articles in reputed journals and conference proceedings, and presented her work at numerous national and international conferences. She also serves as a reviewer, editor, and external examiner for academic journals, conferences, and doctoral research.
Dr. Sah's current research focuses on developing intelligent cybersecurity frameworks that leverage Artificial Intelligence and Machine Learning for cyber threat detection, risk assessment, anomaly detection, and automated incident response. She is equally passionate about interdisciplinary research that applies emerging technologies to healthcare, education, agriculture, and smart digital ecosystems.
A strong advocate of innovation and lifelong learning, Dr. Sah actively mentors students and researchers, encourages collaborative research, and promotes the responsible and ethical adoption of Artificial Intelligence. Her vision is to bridge the gap between cutting-edge research and practical applications by developing intelligent, secure, and sustainable technology solutions that create meaningful societal impact.
Research Interests
- Artificial Intelligence
- Machine Learning
- Cybersecurity
- Data Analytics
- Intelligent Decision Support Systems
- Explainable AI (XAI)
- Deep Learning
- Intelligent Healthcare Systems
- Smart Digital Ecosystems
- Research and Innovation
- International Academic Collaboration
- Curriculum Development
- Doctoral Research Supervision
- AI for Sustainable Development
- Industry–Academia Collaboration
- Ethical and Responsible AI
Aditya Dayal Tyagi
Aditya Dayal Tyagi is a passionate academician, mentor, and researcher. He is specialist in Data Structure, Algorithm Design and Analysis, and Data Base Technologies. He has 20+ years of teaching experience in MCA/B.Tech (CSE/IT) students. He completed his MCA from Dewan Institute of Management Technology Meerut, Uttar Pradesh Technical University (UPTU) – Lucknow and earned his M. TECH in Computer Science and Engineering from GBTU-Lucknow (Previously known as Uttar Pradesh Technical University (UPTU) – Lucknow). He is pursuing his Ph.D from JayPee Institute of Information Technology (Deemed to be University), Noida. His research areas are Information Diffusion, Social Network Analysis, Sentiments Analysis, Signcyption Approach, Deep Learning, and algorithm analysis. He is authored of a book titled "AI-Powered Pricing: Transforming Business with Intelligent Pricing Models." He has one patent and published and presented many research papers in International Journals, International Conferences and National Conferences of repute
Rejwan Bin Sulaiman
Dr. Rejwan Bin Sulaiman is currently serving as a Lecturer in Cyber Security at the University of Law, United Kingdom. He earned his Ph.D. in Artificial Intelligence and Cybersecurity from the University of Bedfordshire, where his doctoral research focused on federated learning-based approaches for secure and privacy-preserving financial AI systems. He has held academic positions at several institutions, including Northumbria University and Arden University.
Dr. Sulaiman’s research spans Cybersecurity, Artificial Intelligence, Computer Vision, and Machine Learning, with particular interest in developing decentralized AI models that enhance data security and user privacy. His work has been published in leading venues such as IEEE, Springer, and CRC Press, contributing to the advancement of secure machine learning frameworks in distributed environments.
He is a Certified Ethical Hacker (CEH) and the founder of STEMResearch.Ai, an initiative that supports and mentors early-career researchers in STEM fields. He is also a Fellow of the Higher Education Academy (FHEA) and has received multiple awards recognizing his innovative teaching practices and dedication to academic excellence.
Pranjali Gajbhiye
Dr. Pranjali Gajbhiye is currently working as a Neuroscientist at Woxsen University, Hyderabad, India, with a strong academic and industry background in biomedical signal processing. With two years of hands-on experience in the BCI-based healthcare industry, she specializes in EEG and fNIRS signal processing using wearable sensing technologies. She holds a PhD in Biomedical Signal Processing (ECE) from BITS Pilani, an M.Tech in Communication System Engineering from VNIT Nagpur, and a B.Tech in ECE from Nagpur University. Her research interests include biomedical signal processing, image and video processing, medical image analysis, and IoT applications in healthcare. She has authored 12+ research articles, contributed to multiple book chapters, and presented at numerous international conferences. She holds 5 patents (published), and serves as a book editor. Her work is published in Q1 journals, including IEEE Transactions on Instrumentation and Measurement. She also contributes academically as a Review Editor for the Q1 journal Frontiers in Physiology (Impact Factor 4.13)
Descriere
Cyber Resilience: Federated Learning and Adaptive AI Through BCI and Neurotechnological Synergy explores the transformative role of artificial intelligence, federated learning, brain–computer interfaces (BCIs), and neurotechnology in strengthening modern cybersecurity.