A Special Issue on: Machine Learning and Block-chain based solution for privacy and access control in IoT
In recent years, Blockchain technology, in conjunction with Machine Learning, has been getting special scrutiny from both academic institutions and commercial businesses. The Internet of Things (IoT) is resource constrained environment and vulnerable to threats Blockchain is a revolutionary system that efficiently records data and transactions by combining decentralized data storage, consensus procedures, point-to-point transmission, and encryption techniques. On the other hand, machine learning is a process that involves extracting inferences from a massive amount of data by locating patterns, identifying anomalies, and establishing links within the data. It is important to look into the possibility of adding machine learning and analysis to the underlying frameworks of current and future applications that use Block chain technology for its unique qualities.
The main goal of this special issue is to collect and present the state-of-art light weight security solution to handle privacy and access control issue in IoT environment. We encourage researchers and engineers from academia, industry and government to submit high-quality original research articles that represent novel theories, methodologies, case studies and applications. All submitted papers will be peer-reviewed and selected based on both their quality and their relevance to the theme of this special issue.
Recommended topics (but not limited to)
The following are the recommended topics for this special issue:
- Data Security and Computing by using Machine Intelligence and Blockchain
- IoT Cloud Data Privacy Computing, Differential Privacy and Homomorphic Encryption
- Zero Trust Authentication and Dynamic Access Control over IoT ans Big Data
- Federated Learning/Deep Learning Architecture, Model an Algorithm for IoT Security
- Advancement of blockchain in IoT and Cloud server Security
- Big data algorithms, tools, applications and services using blockchain
- Blockchain-based decision-making schemes for IoT security
- Real/Industrial application-based Blockchain systems for IoT
- Light -weight Security and privacy aspects of Blockchain
- Performance optimization for blockchain-enabled big data applications
Submission deadline: 31 December, 2023
Authors notification: 31 March, 2024
Revised version deadline: 15 May, 2024
Completion of Special Issue: June, 2024
Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.
During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.
Lead: Kumar Abhishek, National Institute of Technology Patna, India, email: email@example.com
Dr. Kumar Abhishek received his Computer Engineering Bachelors from Biju Pattanaik University of Technology, Master from Anna University and PhD from NIT Patna. He has an experience of 13 years in Academic and research. He is presently working as Assistant Professor in Dept. of Computer Science and Eng., NIT Patna. He has published 100+ peer-reviewed research articles including SCI & Scopus indexed International Journals apart from Book chapters & numerous conference proceedings. He also member of IEEE, ACM and ISTE
Sadia Din, Department of Information and Communication Engineering, Yeungnam University, South Korea, email: mailto:firstname.lastname@example.org
Sadia Din received the master’s degree in computer science from Abasyn University, Islamabad, Pakistan, in 2015, and the Ph.D. degree in data science from Kyungpook National University, South Korea, in 2020. In 2015, she was a Visiting Researcher with the CCMP Laboratory, Kyungpook National University, South Korea, where she was working on big data and the Internet of Things. She was working as a Postdoctoral Researcher with Kyungpook National University, South Korea, from March 2020 to August 2020. She is currently working as an Assistant Professor with the Department of Information and Communication Engineering, Yeungnam University, South Korea. During her Ph.D., she was working on various projects, including demosaicking and denoising using machine/deep learning and artificial learning. Furthermore, she extended her research toward the Internet of Things, 5G, and big data analytics. At the beginning of her research career, she has published more than 60 journals and conferences, including IEEE Internet of Things Journal (IEEE IoT), IEEE Transactions on Industrial Informatics (IEEE TII), IEEE Wireless Communications, IEEE GLOBECOM, IEEE LCN, and IEEE INFOCOM. Her research interests include demosaicking and denoising using machine/deep learning, artificial learning, big data analytics, 5G, and the IoT. In addition, she was a recipient of two Korean patents in 2019 and 2020. Moreover, she was a recipient of two international awards, such as the Research Internship at the CCMP Research Laboratory, Kyungpook National University, in June 2015, and the CSE Best Research Award at Kyungpook National University in October 2019. She was also the Chair of the IEEE International Conference on Local Computer Networks (LCN 2018). She is also serving as a Guest Editor for journals of Wiley and Big Data, and Micro Processor and Microsystem. At IEEE LCN 2017 in Singapore, she has chaired couple of sessions.
Abdul Wahid, National University of Ireland, Galway, email: email@example.com
Dr. Abdul Wahid is a postdoctoral researcher in the School of Computer Science at the National University of Ireland, Galway. Prior to this, he worked as a research engineer at the Institut de Recherche en Informatique, Mathématiques, Automatique et Signal (IRIMAS), University of Upper Alsace, France, in collaboration with ENYGMA and funded by the Région Grand-Est. From September 2021 to September 2022, he was a postdoctoral research fellow on a DETSI project in the INFormatique et RESeaux (INFRES), Telecom Paris, Institute Polytechnique de Paris, France. He obtained his bachelor's degree in Information Technology from MIT Muzaffarpur, India, his master's degree from the Department of Computer Science and Engineering at the National Institute of Technology Patna, India, and his Ph.D. in Computer Science \& Engineering from the Indian Institute of Technology (Indian School of Mines), Dhanbad, India. Before joining as a Ph.D. scholar at IIT (ISM) Dhanbad, he worked as an Assistant Professor in the Department of Computer Engineering at the National Institute of Technology Kurukshetra, Haryana, India. He has many research articles published in reputed conferences and journals. His research interests include Anomaly Detection, Fraud Detection, Data Mining, Machine Learning, and Artificial Intelligence. He is a reviewer for several reputed journals and conferences, including Transactions on Management Information Systems (ACM), IEEE Transactions on Emerging Topics in Computational Intelligence, Transactions on Computer-Aided Design of Integrated Circuits and Systems, Neurocomputing, Future Generation Computer Systems, Expert Systems and Applications, etc. He has also served as a member of the technical program committee at many reputed international conferences and has been serving as a guest editor for reputed journals.
Dr Houbing Song, University of Maryland, Baltimore County (UMBC), Baltimore, MD 21250 USA, email: firstname.lastname@example.org , email@example.com
Houbing Song (M’12–SM’14-F’23) received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012. He is currently a Tenured Associate Professor, the Director of NSF Center for Aviation Big Data Analytics (Planning), and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab,www.SONGLab.us), University of Maryland, Baltimore County (UMBC), Baltimore, MD. Prior to joining UMBC, he was a Tenured Associate Professor of Electrical Engineering and Computer Science at Embry-Riddle Aeronautical University, Daytona Beach, FL. He serves as an Associate Editor for IEEE Transactions on Artificial Intelligence (TAI) (2023-present), IEEE Internet of Things Journal (2020-present), IEEE Transactions on Intelligent Transportation Systems (2021-present), and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present). He was an Associate Technical Editor for IEEE Communications Magazine (2017-2020). He is the editor of eight books, the author of more than 100 articles and the inventor of 2 patents. His research interests include cyber-physical systems/internet of things, cybersecurity and privacy, and AI/machine learning/big data analytics. His research has been sponsored by federal agencies (including National Science Foundation, US Department of Transportation, and Federal Aviation Administration, among others) and industry. His research has been featured by popular news media outlets, including IEEE Global Spec’s Engineering360, Association for Uncrewed Vehicle Systems International (AUVSI), Security Magazine, CXOTech Magazine, Fox News, U.S. News & World Report, The Washington Times, and New Atlas. Dr. Song is an IEEE Fellow, an ACM Distinguished Member, and an ACM Distinguished Speaker. Dr. Song has been a Highly Cited Researcher identified by ClarivateTM (2021, 2022) and a Top 1000 Computer Scientist identified by Research.com. He received Research.com Rising Star of Science Award in 2022 (World Ranking: 82; US Ranking: 16). Dr. Song was a recipient of 10+ Best Paper Awards from major international conferences, including IEEE CPSCom-2019, IEEE ICII 2019, IEEE/AIAA ICNS 2019, IEEE CBDCom 2020, WASA 2020, AIAA/ IEEE DASC 2021, IEEE GLOBECOM 2021 and IEEE INFOCOM 2022.
Chinmay Chakraborty, Birla Institute of Technology, Mesra, Jharkhand, India, email: firstname.lastname@example.org
Dr. Chinmay Chakraborty, SMIEEE is an Assistant Professor in Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India and he completed Post-doctoral fellow from Federal University of Piauí, Brazil. His main research interests include the Internet of Medical Things (IoMT), Wireless Body Sensor Networks, Wireless Networks, Telemedicine, m- Health/e-health, and Medical Imaging. Dr. Chakraborty has published 190+ articles at reputed international journals, conferences, book chapters, 22+ books and 20+ special issues. He is an Editorial Board Member in the different Journals and Conferences. He serves as a Guest Editor of MDPI-FI Journal, Wiley-ITL, BSR, Springer-ANT, IJSAEM, EDS, and Lead Guest Editors of IEEE-JBHI, IEEE-TII, ACM-TALIP, ACM-JDIQ, IEEE-TCSS, Hindawi- JHE, Mary Ann Liebert - Big Data J., IGI-IJEHMC, Springer – MTAP, INSCL, TechScience CMC, Inderscience- IJNT, BenthamScience -Current Medical Imaging, Journal of Medical Imaging and Health Informatics, Lead Series Editor of CRC- Advances in Smart Healthcare Technologies, and also Associate Editor of International Journal of End-User Computing and Development, Journal of Science & Engineering, IET-The Journal of Engineering, Int. Journal of Strategic Engineering, and has conducted a session of SoCTA-19, ICICC – 2019, Springer CIS 2020, SoCTA-20, SoCPaR 2020, and also a reviewer for international journals including IEEE Access, IEEE Sensors, IEEE Internet of Things, IEEE TII, IEEE JBHI, IEEE Sensors, Elsevier, Springer, Taylor & Francis, IGI, IET, TELKOMNIKA Telecommunication Computing Electronics and Control, and Wiley. Dr. Chakraborty is co-editing several books on Smart IoMT, Healthcare Technology, and Sensor Data Analytics with Elsevier, CRC Press, IET, Pan Stanford, and Springer. He has served as a Publicity Chair member at renowned international conferences including IEEE Healthcom, IEEE SP-DLT.