This book constitutes the proceedings of the 22nd International Conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2021, which took place in Guangzhou, China, during December 17-19, 2021. The 24 full papers and 34 short papers included in this volume were carefully reviewed and selected from 97 submissions. The papers are categorized into the following topical sub-headings: networking and architectures, software systems and technologies, algorithms and applications, and security and privacy.

This book comprises select peer-reviewed contributions from the 6th International Conference on Production and Industrial Engineering (CPIE - 2019). The volume focuses on latest research in the field of Industrial and Systems Engineering, and its allied areas. Articles on variety of topics such as Human Factors Engineering, Lean Manufacturing, Six Sigma, Logistics and Supply Chain Management, Operations Research, Quality Engineering, Measurement and Control, Reliability and Maintenance Engineering, Green Supply Chain Management, Modelling and Simulation, Sustainability, Technology Management, Agile and Flexible Manufacturing, Technology Management and Computer Aided Manufacturing are discussed in this book. Given the range of topics covered, the book will be useful for students, researchers, and professionals interested in different areas of Industrial and Systems Engineering.

Large-scale attacks generated by fast spreading worms and viruses have emerged as a major threat to the Internet. These worms are capable of infecting and crippling substantial portions of the Internet as well as the enterprise networks of large public and private agencies in a very short time. This dissertation work studies the behavior of such viruses and examines the problem of their detection and containment. It develops a simulation testbed to study the propagation and threat potentials of self- propagating viruses. Using the testbed, a new approach is developed for detecting self-propagating worms/viruses based on statistical anomaly detection. The approach assumes that a key characteristic of a worm/virus attack is an increase in application based network traffic, which will eventually overwhelm servers and clients. The effectiveness of the detection approach has been tested for email based viruses in an intranet setting. The report concludes with results of experiments using a novel approach for cleaning up virus infections, based on the model of "predators" in an ecosystem.