This book covers technical contributions that have been submitted, reviewed and presented at the 22nd annual event of International conference on Information Technology: New Generations (ITNG) The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security and health care are among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics.

Autorentext

Shahram Latifi , an IEEE Fellow (2002), received the Master of Science and the PhD degrees both in Electrical and Computer Engineering from Louisiana State University, Baton Rouge, in 1986 and 1989, respectively. He is currently a Professor of Electrical Engineering at the University of Nevada, Las Vegas. Dr. Latifi is the co-director of the Center for Information Technology and Algorithms (CITA) at UNLV. He has designed and taught undergraduate and graduate courses in the broad spectrum of Computer Science and Engineering in the past four decades. He has given keynotes and seminars on machine learning/AI and IT-related topics all over the world. He has authored over 250 technical articles in the areas of networking, cybersecurity, image processing, biosurveillance, biometrics, document analysis, fault tolerant computing, parallel processing, and data compression. His research has been funded by NSF, NASA, DOE, DoD, Boeing, Lockheed and Cray Inc. Dr. Latifi was an Associate Editor of the IEEE Transactions on Computers (1999-2006), an IEEE Distinguished Speaker (1997-2000), and Co-founder and General Chair of the IEEE Int'l Conf. on Information Technology (2004-2015). Dr. Latifi is the recipient of several research awards, the most recent being the Barrick Distinguished Research Award (2021). Dr. Latifi was recognized to be among the top 2% researchers around the world in December 2020, according to Stanford top 2% list (publication data in Scopus, Mendeley). He is a Registered Professional Engineer in the State of Nevada.

Inhalt

Adaptive GAN-Based Defense Against Data Poisoning in Federated Learning.- Password Security in Practice: An Appraisal Using Users' Perception and Machine Learning.- Security and Privacy for LLMs and LMMs Across Key Sectors: A Literature Survey.- Malicious URL Detection Using Machine Learning.- Zero-day Malware detection using Fine-Tuned MobileNetV2 and Open-set Classification.