Advancements in IoT, Cyber Security and Cloud Computing
Description
This book features original, peer-reviewed research papers presented at the International Conference on Recent Trends in Artificial Intelligence and Data Sciences-CONFLUENCE 2025. It aims to showcase the latest developments in various fields of data science and computational techniques. The topics covered include artificial intelligence, machine learning, data science, deep learning, soft computing, and other computational methodologies. The papers share recent findings on the aforementioned topics, making this book is a valuable resource for researchers, scientists, industry professionals, and students alike.
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Persons
Sanjeev Thakur earned his bachelor's and master's degrees from the University of Delhi and subsequently completed his PhD from Amity University. He began his career in industry, working as an engineer for about four years, followed by a year as a Research Associate at IIT Delhi before transitioning to academia. Dr. Thakur has over 25 years of experience in teaching, research, and academic administration. He serves as Professor and Head of Department at Amity School of Engineering and Technology, and as Coordinator for the Network and Cloud Computing Research Group at ASET Noida. He has authored and co-authored over 60 papers in journals and conferences of international repute.
Rakesh Garg is working as an associate professor in the Department of Computer Science & Engineering at Gurugram University, Gurugram, Haryana, India. His research interests include component-based software engineering, software reliability, and multi-criteria decision-making optimization. He has published more than 50 research papers in highly reputed international journals indexed.
Shilpi Sharma is a professor in the Department of Computer Science and Engineering at Amity University, Uttar Pradesh, with over 25 years of teaching experience. Her research interests encompass network security, quantum computing, cyber security, cloud computing and social networks, focusing on securing networks, protecting systems from cyber threats, and exploring the dynamics of social networks. Dr. Sharma has authored over 100+ research papers published in international journals and presented at conferences, contributing significantly to the academic and practical understanding of technology and security challenges. She has actively participated in the academic community as a Technical Program Committee member, reviewer, and session chair for various international conferences. Additionally, Dr. Sharma has filed 7 patents, 2 of which have been granted. Dr. Sharma is also a member of several esteemed organizations, including IEEE, ACM, IET, IAENG, and UACEE and is currently guiding 04 research scholars.
Debabrata Samanta is the Department Chair and Assistant Professor at the Department of Computing and Information Technologies, Rochester Institute of Technology-RIT Tirana, located on Asim Vokshi Street, Tirana, Albania, Europe. His expertise spans a wide range of fields including SAR image analysis, video surveillance, heuristic algorithms for image classification, deep learning frameworks for detection and classification, blockchain, statistical modeling, wireless ad hoc networks, and natural language processing. He has completed six consultancy projects and holds 22 patents (including 4 Indian design patents and 2 granted Australian patents, with 16 Indian patents published), along with 2 copyrights. Dr. Samanta has authored and co-authored over 260 research papers in international journals and conference proceedings. He has co-authored 13 books, co-edited 23 books, and contributed to 17 book chapters.
Content
Deep Learning Based Human Activity Recognition for Sports and Fitness Performance Enhancement.- Beyond the Pitch-Deep Learning in Cricket Performance Analysis.- A Deep Learning Approach Using Dermoscopy Images for Classification and Diagnosis of Skin Diseases.- Stacked CNN: Deep Networks for Brain Tumor Classification.- Bi-DCGAN: Improving Facial Image Synthesis from Textual Descriptions with Integrated Deep Learning Models.- A Deep Dive into NLP Based Text Emotion Analysis.- A Hybrid Approach for Efficient and Precise Food Detection using YOLOv9 and RCNN.- Image Denoising with Generative AI: A GAN-CNN Based Approach.- Revolutionizing Brain Tumour Detection with Vision Transformers (ViT).- Analysis of Brain Tumors: A Comparative Study of YOLOv5 and U-NET Architecture.- Predicting Agitation in Dementia patients using IOT sensor data and deep learning techniques.- Time Series Deep Learning Models to Predict and Analyze Air Quality Index of Indian Cities.- vKavach: A Real-Time Attack Resilient Malware Detector in Virtualization Environment.- Malware Detection Using Cyber Intelligence.- Framework for Malware Detection in IoT Resource Allocation.- Key Exchange Protocol with (p, q)-Transform using BLAKE3 Hashing.