Del 739 - Lecture Notes in Electrical Engineering

Information Science and Applications

Proceedings of ICISA 2020

Inbunden, Engelska, 2021

Av Hyuncheol Kim, Kuinam J. Kim, Suhyun Park

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This book presents select proceedings of 11th International Conference on Information Science and Applications 2020 (ICISA 2020) and provides a snapshot of the latest issues encountered in technical convergence and convergences of security technology. It explores how information science is core to most current research, industrial and commercial activities and consists of contributions covering topics including Ubiquitous Computing, Networks and Information Systems, Multimedia and Visualization, Middleware and Operating Systems, Security and Privacy, Data Mining and Artificial Intelligence, Software Engineering, and Web Technology. Also the proceedings introduce the most recent information technology and ideas, applications and problems related to technology convergence, illustrated through case studies, and reviews converging existing security techniques. Through this book, readers can gain an understanding of the current state-of-the-art information strategies and technologies of convergence security.

Produktinformation

Utgivningsdatum2021-04-03
Mått155 x 235 x undefined mm
FormatInbunden
SpråkEngelska
SerieLecture Notes in Electrical Engineering
Antal sidor398
FörlagSpringer Verlag, Singapore
ISBN9789813363847

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Elektronik och kommunikationer inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it
Nätverk och kommunikation inom Data och it
IT-säkerhet inom Data och it

Hyuncheol Kim is Professor in the Department of Computer Science at Nam Seoul University, Korea. He is Associate Editor of Software Networking Journal. He received his B.S., M.S., and Ph.D. degrees in Computer Engineering from Sungkyunkwan University, Korea. His research interests include mobile and wireless networking, software-defined networking (SDN), and network function virtualization (NFV) and artificial intelligence. Kuinam J. Kim is Professor and Chairman of the Convergence Security Department, Kyonggi University, Korea. He is Founding Editor-in-Chief of the ICAT Transactions on Convergence IT Security and serves on the advisory editorial board of the Convergence Security Journal. He is also President of the Korea Industry Security Forum and Korea Convergence Security Association. His research interests include cloud computing, wireless and mobile computing, digital forensics, video surveillance, and convergence security. He has published extensively in these areas and received several best paper awards from journals and conferences. He received his B.S. in Mathematics from the University of Kansas (www.ku.edu) and his Ph.D. in Industrial Engineering from Colorado State University (1994). He is currently Professor at convergence security department, Kyonggi University. Suhyun Park is Professor in the Department of Computer Engineering and Director of Information and Communication Center, Dongseo University, Korea. She is also Vice Chair of Korea Institute of Information and Communication Engineering. She received her B.S., M.S., and Ph.D. degrees in Computer Science from Pusan National University, Korea.Her research interests include artificial intelligence, mobile computing, and cloud computing systems.

Experience and prospects of tele-health technologies.- Exploring the Effects of Network Topology Layers on Quality of Service Mechanisms in the Context of Software-Defined Networking.- Image Background Subtraction and Partial Stylization based on Style Representation of Convolutional Neural Networks.- Multi-source log clustering in distributed systems.- A Study on Classification and Integration of Research on both AI and Security in the IoT Era.- Safe Internet: An Edutainment Tool for Teenagers.- Predictive Analytics Service for Security of Blockchain and Peer-to-Peer Payment Solutions.- Deterring SLCAs by Establishment of ACSC based on IPP YoungYungShin 9.30.- Research on life cycle model of data for handling Big Data-based security incident.- Feature Selection Based on a Shallow Convolutional Neural Network and Saliency Maps on Metagenomic Data.