Data Mining and Information Security

Proceedings of ICDMIS 2025, Volume 5
Erscheinungsjahr 2026
ISBN: 978-3-032-21900-8
Verlag: Springer

Buch, Englisch, Band 1915, 553 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 855 g

Reihe: Lecture Notes in Networks and Systems

This book features research papers presented at the International Conference on Data Mining and Information Security (ICDMIS 2025) held in Phnom Penh in collaboration with Eminent College of Management & Technology (ECMT) and University of Puthisastra, Cambodia, during October 7–8, 2025. The book is organized in five volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT), and information security.

Zielgruppe

Research

Autoren/Hrsg.

Dutta, Soumi

Bhattacharya, Abhishek

Kumar, Rajesh

Slowik, Adam

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

Design of robust, scalable, and low-resource CNN optimizer for practical agricultural applications.- Application of AI in Supervising and Monitoring Sewage Treatment Plant.- Next-Gen Clubfoot Detection: An Intelligent Deep Learning Framework for Accurate Identification and Classification of Congenital Clubfoot Deformities.- Reliable Energy Consumption Prediction: Leveraging Deep Learning with SHAP and LIME for Transparency.- Dust Cloud Detection: A Machine Learning Approach.- Evaluating the Efficacy of AI and Machine Learning Models for Early Alzheimer's Disease Detection Using Multi-Modal Data.- Enhanced Fabric Defect Detection: A Deep Learning Approach.- AI-Driven Crop Selection: Enhancing Agricultural Productivity with Machine Learning.- Personalized Fashion Recommendation System using Deep Models based on Dempster Shafer Theory.- Enhanced Breast Cancer Analysis Using Support Vector Machine based on Phenotypical Features with LIME Interpretability.- BioFuseNet: A Multi-Branch Autoencoder with Gene-Set-Aware Fusion for Classification of Gene Expression Profiles.- Enhancing Microscopic Images through Lucy-Richardson Deconvolution, Dark Channel Prior, and Adaptive Histogram Equalization.- Protection of Personal Data in the arbitration between the GDPR and the DPDP: What are the differences?.- Feature Selection Based Crime Prediction using Machine Learning.

Über Autor(innen)

Dr. Soumi Dutta is Professor at Sister Nivedita University (SNU) at New Town, Kolkata, India. She has completed her Ph.D. (CST), IIEST, Shibpur. She received her B.Tech. (IT) and M.Tech. (CSE) securing 1st position (Gold medallist), from MAKAUT. She is certified as Publons Academy Peer Reviewer, 2020 and Certified Microsoft Innovative Educator, 2020. Her research interests are Data Mining, Information Retrieval, Online Social Media Analysis, and Image Processing. She has published more than 60 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. She has 40 Books and Book Chapters in Taylor & Francis Group and IGI Global. She is peer reviewer and TPC member in different international journals. She is an active member of several technical functional bodies such as CSI, IEEE, IFERP, MACUL, SDIWC, Internet Society, ICSES, ASR, AIDASCO, USERN, IRAN, IAENG. She has published 10 patents and 1 copyright.

Dr. Abhishek Bhattacharya is Professor at Sister Nivedita University, India. He has completed his Ph.D. (CSE), BIT, Mesra. He is certified as Publons Academy Peer Reviewer, 2020. His research interests are Data Mining, Cyber security, and Mobile Computing. He has published 55 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. He has 3 Book Chapters in Taylor & Francis Group EAI. He is a peer reviewer and TPC member in different international journals. He was the editor in IEMIS 2020, IEMIS 2018, IEMIS 2022, ICIDA 2022, ICIDA 2023, CIIR 2023, CIIR 2024, ICDMIS 2024, ICDMIS 2025, ICIDA 2025 and special issues in IJWLTT. He is the member of several technical functional bodies such as IEEE, IFERP, MACUL, SDIWC, Internet Society, ICSES, ASR, AIDASCO, USERN, IRAN, IAENG. He has published 3 patents and 20 books.

Dr. Rajesh Kumar, (SMIEEE, Fellow IET(UK), Fellow IE(I), Fellow IETE, LMCSI, LMISTE) received the B.Tech. (Hons.) degree in Electrical Engineering from the National Institute of Technology (NIT), Kurukshetra, India, 1994, the M.E. (Hons.) and Ph.D. degrees in Power Systems and Intelligent Systems from the Malaviya National Institute of Technology (MNIT) Jaipur, Rajasthan, India 1997, and 2005, respectively. He was a postdoctoral research fellow with the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore from 2009 to 2011. Currently, he is working as a professor of Artificial Intelligence at the Department of Human Anatomy and Physiology, Faculty of Health Sciences, University of Johannesburg, South Africa and a professor in the Department of Electrical Engineering, MNIT, Jaipur, India. His research interests focus on Intelligent Systems, Data Driven algorithms, Analytics, and Healthcare. He holds 18 patents/patent applications and published over 750 research articles in international conferences and journals.

Dr. Adam Slowik (Senior Member, IEEE) received the B.Sc. and M.Sc. degrees in computer engineering and electronics, in 2001, and the Ph.D. degree in electronics with distinction from the Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland, in 2007, respectively, and the Dr. habil. degree in computer science (intelligent systems) from the Department of Mechanical Engineering and Computer Science, Czestochowa University of Technology, Czestochowa, Poland, in 2013. Since October 2013, he has been an associate professor with the Department of Electronics and Computer Science, Koszalin University of Technology. He is an author or co-author of more than 180 refereed articles in international journals, two books, and conference proceedings, including two invited talks. His research interests include soft computing, machine learning, neural networks, fuzzy systems, computational intelligence, bio-inspired optimization algorithms, and their engineering applications. Dr. Slowik is a reviewer for many international scientific journals.