Advancing Cyber Threat Detection Through Quantum and Edge Computing

• #1. A Comprehensive Introduction to Cyber Threat Detection Through Quantum Computing and Comparative Study of Classical and Quantum-Enhanced Convolutional Neural Networks
• #2. Quantum AI for Cybersecurity and Threat Intelligence
• #3. Quantum-Enhanced Edge Computing for Robust Cyber Threat Detection
• #4. Guardians of the Grid: Navigating Ethical Dilemmas and Regulatory Frameworks in Cyber Threat Detection
• #5. Secure Healthcare Data Sharing Using Federated Learning, Blockchain, and Quantum Cryptography
• #6. Synergizing Edge AI and Quantum Machine Learning for Real-Time Cyber Threat Mitigation
• #7. Quantum-Enhanced Machine Learning for Next-Gen Cyber Defense
• #8. Anomaly Detection Using Quantum Neural Networks: A Quantum-Driven Approach to Cyber Threat Identification
• #9. Ethical Challenges and Regulatory Considerations in Quantum AI-Powered Cyber Threat Detection
• #10. QINN-Based Approach to Detect Anomalies in High-Dimensional Secure Data

Shenson Joseph 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 many national and international events and actively contributes to editorial boards and conferences. He has earned a master’s degree in data science and a second master’s degree in electrical & computer engineering. He is IEEE senior member and associated with ACM and AAAI (association for the advancement of artificial intelligence).

Dr. C Kishor Kumar Reddy , 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 12 years. He has published more than 90 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 15 edited books. He is the member of ISTE, CSI, IAENG, UACEE, IACSIT

Asegul Hulus serves as an assistant professor while also being recognised as a fellow of the Higher Education Academy (FHEA). She is a distinguished researcher and author specialising in the field of computing. She holds memberships in esteemed organisations, including the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), among others. Additionally, she possesses skills in graphic design, video editing, audio production, and video game proficiency. Dr Hulus serves as a chair, chief editor, and peer reviewer for numerous journals, conferences, and publication houses. Furthermore, she holds a prominent position as one of the founding leaders in her field. Finally, she serves as a mentor for the Women4Cyber Foundation and holds various leadership positions in professional computing committees, such as the Association for Computing Machinery's Council on Women in Computing (ACM-W).

Prof. Dr. Tatjana Sibalija (BSc, MSc, PhD in Mechanical Engineering, from Faculty of Mechanical Engineering, University of Belgrade) is Full Professor at the Faculty of Computing, Union University, Belgrade. Her research interest includes artificial intelligence, data science, manufacturing and industrial engineering, process modelling, design and optimisation. She is the editor of 3 books; author of 6 books, 12 book chapters, 130+ papers published in peer-reviewed international journals / presented at refereed international conferences (h-index=20, i10-index=30), including several invited keynote speeches. She has served as a chair of many conference sessions, a member of 50+ scientific program committees of international conferences, a member of the editorial board and guest editor of several international scientific journals. She has been awarded eight awards and honours. Since 2009, she has been appointed FP7 / Horizon 2020 / Horizon Europe (EU Research Framework Programmes) expert / advisor on the projects review, selection and progress monitoring