International Conference on Smart Systems and Advanced Computing (SysCom 2022)

This book presents the International Conference on Smart Systems and Advanced Computing (SysCom 2022) that features scientific work on smart solution concepts. It covers collective computational intelligence, which encompasses smart device interactions, smart surroundings, and smart ability to interact, as well as information technology support for these areas. It concentrates on cutting-edge research and technologies in smart systems and advanced computing for intelligent autonomous systems. The objectives of SysCom 2022 are to provide a premier international platform for deliberations on strategies, recent trends, innovative approaches, discussions, and presentations on the most recent development in the field of smart system technology from the perspective of providing awareness and its best practices for the real world.

Includes recent research on recent smart devices and advanced computing challenges and developments Proceedings of the 2nd Int. Conference on Smart Systems and Advanced Computing (SysCom 2022) Written by experts in the field

Autorentext

Nadia Nedjah received the engineering degree in computer science, the M.Sc. degree in system engineering and computation from the University of Annaba, Algeria, and the Ph.D. degree in computation from The University of Manchester Institute of Science and Technology, Manchester, U.K. She is currently Associate Professor at the Department of Electronics Engineering and Telecommunications, Faculty of Engineering, Rio de Janeiro State University, Rio de Janeiro, Brazil. Her research interests include functional programming, embedded systems, reconfigurable hardware design, and cryptography.

Brij B. Gupta is working as Director of International Center for AI and Cyber Security Research, Incubation and Innovations, and Full Professor at the Department of Computer Science and Information Engineering (CSIE), Asia University, Taiwan. In more than 17 years of his professional experience, he published over 500 papers in journals/conferences including 35 books and 10 patents with over 21000 citations. He has received numerous national and international awards including Canadian Commonwealth Scholarship (2009), Faculty Research Fellowship Award (2017), MeitY, GoI, IEEE GCCE Outstanding and WIE Paper Awards, and Best Faculty Award (2018 & 2019), respectively. Prof. Gupta was selected for 2022 Clarivate Web of Science Highly Cited Researchers in Computer Science. He was also selected in the 2022, 2021, and 2020 Stanford University's ranking of the world's top 2% scientists. He is also Visiting/Adjunct Professor with several universities worldwide. He is also IEEE Senior Member (2017) and selected as 2021 Distinguished Lecturer in IEEE CTSoc. Dr. Gupta is also serving as Member-in-Large, Board of Governors, IEEE Consumer Technology Society (2022-2024). Prof. Gupta is also leading IJSWIS, IJSSCI, STE, and IJCAC as Editor-in-Chief. Moreover, he is also serving as Lead Editor of a book series with CRC and IET press. He also served as TPC Member in more than150 international conferences also serving as Associate/Guest Editor of various journals and transactions. His research interests include information security, cyber-physical systems, cloud computing, blockchain technologies, intrusion detection, AI, social media, and networking.

Gregorio Martínez Pérez received the bachelor's and Ph.D. degrees in computer science from the University of Murcia, Murcia, Spain, in 1998 and 2003, respectively. He is currently Full Professor at the Department of Information and Communications Engineering, University of Murcia. He has authored and co-authored more than 160 papers in national and international conference proceedings, magazines, and journals. He is working as Principal Investigator in many different national and European IST research projects related to the topics of his research interests, which include cybersecurity and networking.

Inhalt

Traffic Flow Prediction with Heterogenous Data using a Hybrid LSTM BILSTM Model.- Radial Basis Neural Network based Distributed Denial of Services (DDoS) Attack Detection.- Skin Lesion Classification using CNN and Transformer Networks for Computer-Assisted Diagnosis.- Blockchain consensus layer security issues: classification and exploration.- Detection of Distributed Denial of Service Attack Using Software-Defined Network with Dynamic Entropy.