This book contains selected papers from the 7th International Conference on Information Science and Applications (ICISA 2016) 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. The contributions describe the most recent developments in information technology and ideas, applications and problems related to technology convergence, illustrated through case studies, and reviews converging existing security techniques. Through this volume, readers will gain an understanding of the current state-of-the-art information strategies and technologies of convergence security. The intended readers are researchers in academia, industry and other research institutes focusing on information science and technology.

This book presents selected papers from the 10th International Conference on Information Science and Applications (ICISA 2019), held on December 16–18, 2019, in Seoul, Korea, and provides a snapshot of the latest issues regarding technical convergence and convergences of security technologies. It explores how information science is at the core of most current research as well as industrial and commercial activities. The respective chapters cover a broad range of 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, as well as applications and problems related to technology convergence, which are reviewed and illustrated with the aid of case studies. Researchers in academia, industry, and at institutes focusing on information science and technology will gain a deeper understanding of the current state of the art in information strategies and technologies for convergence security. ​

This book constitutes the refereed proceedings of the 5th International Conference on Future Data and Security Engineering, FDSE 2018, held in Ho Chi Minh City, Vietnam, in November 2018. The 28 revised full papers and 7 short papers presented together with two papers of keynote speeches were carefully reviewed and selected from 122 submissions. The selected papers are organized into the following topical headings: security and privacy engineering; authentication and access control; big data analytics and applications; advanced studies in machine learning; deep learning and applications; data analytics and recommendation systems; Internet of Things and applications; smart city: data analytics and security; and emerging data management systems and applications.

The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.