Advancing Cyber Threat Detection Through Quantum and Edge Computing. This item is unavailable.
Language: English
Published by Information Science Reference, 2025
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- Title
- Advancing Cyber Threat Detection Through Quantum and Edge Computing
- Publisher
- Information Science Reference
- Publication year
- 2025
- Condition
- New
- Binding
- HRD
- Language
- English
- ISBN 13
- 9798337335513
- Item weight
- 866 grams
As cyber threats grow in scale, sophistication, and frequency, traditional detection methods struggle to keep pace. To address this landscape, researchers and organizations turn to emerging technologies like quantum computing and edge computing. Quantum computing offers increased processing power, capable of analyzing complex data patterns and encryptions. Meanwhile, edge computing enables real-time threat detection and increases response times. By combining these two technologies, it creates smarter, faster, and more adaptive cybersecurity systems. Further exploration into how the convergence of quantum and edge computing can revolutionize cyber threat detection may pave the way for more resilient defense mechanisms in the digital age. Advancing Cyber Threat Detection Through Quantum and Edge Computing explores how quantum computing and artificial intelligence (AI) reshape the landscape of real-time anomaly detection, predictive analytics, and next-gen cybersecurity. It examines how quantum-enhanced AI models can detect patterns, adapt to emerging threats, and revolutionize security frameworks across industries, from finance and healthcare to national security and cloud infrastructure. This book covers topics such as blockchain, threat intelligence, and neural networks, and is a useful resource for computer engineers, security professionals, academicians, researchers, and data scientists.
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About the Author
Shenson Josep h is a distinguished AI researcher and data science expert. With expertise in Data Science, Analytics, and Artificial Intelligence, he has authored 2 books, and authored more than 6 research papers. Shenson has judged over many national and international events and actively contributes to editorial boards and conferences. He has earned a master's degree in Data Science and second masters degree in Electrical & Computer Engineering.
Kishor Kumar Reddy C. is currently working as Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than 10 years. He has published more than 80 research papers in National and International Conferences, Book Chapters, and Journals indexed by Scopus and others. He is an author for 2 text books and 12 co-edited books. He acted as the special session chair for Springer FICTA 2020, 2022, SCI 2021, INDIA 2022 and IEEE ICCSEA 2020 conferences. He is the corresponding editor of AMSE 2021 conferences, published by IoP Science JPCS. He is the member of ISTE, CSI, IAENG, UACEE, IACSIT.
Kishor Kumar Reddy C. is currently working as Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than 10 years. He has published more than 80 research papers in National and International Conferences, Book Chapters, and Journals indexed by Scopus and others. He is an author for 2 text books and 12 co-edited books. He acted as the special session chair for Springer FICTA 2020, 2022, SCI 2021, INDIA 2022 and IEEE ICCSEA 2020 conferences. He is the corresponding editor of AMSE 2021 conferences, published by IoP Science JPCS. He is the member of ISTE, CSI, IAENG, UACEE, IACSIT.
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