Data Science and Security

Proceedings of IDSCS 2025, Volume 1
Erscheinungsjahr 2026
ISBN: 978-3-032-24359-1
Verlag: Springer

Buch, Englisch, 366 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

This book presents the best papers from the International Conference on Data Science for Computational Security (IDSCS 2025), hosted by CHRIST (Deemed to be University), India, and technically sponsored by The Tejas Scientific Researcher Foundation, India, held on November 14–15, 2025. This book covers current research in data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithm design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing.

Zielgruppe

Research

Autoren/Hrsg.

Shukla, Samiksha

Sayama, Hiroki

Tiwari, Kapil

George, Jossy Paul

Kureethara, Joseph Varghese

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen

Inhaltsverzeichnis

Unmanned Underwater Vehicle Magnetic Stealth Prediction Multiobjective Design.- Real-Time Point Cloud Simplification via Localized SVD with Adaptive Thresholding.- Enhancing Sepsis Detection Comparing Different Classification Methods Combined with Genetic Algorithm and Recursive Feature Elimination.-  AI-Guided Candidature Enhancement: A Counterfactual and Interpretability Framework for Recruitment Decisions.- Artificial Intelligence for Quality Control in Multi-Tier Supply Chains: Frameworks, Challenges, and Future Directions.- Decoding Breast Cancer Subtypes: A Deep Learning Approach to Gene Expression Profiling.- Quantum-integrated Generative Classification and Regularized Regression Algorithms for optimization of Travelling Salesman Problem.- Comprehensive Analysis of Machine Learning and Ensemble Models for Malicious URL Detection.- Deep Hybrid Model for Maternal Health Risk Classification in Pregnancy.- Smart Spend Analyzer: ML-Powered SMS Parsing for Financial Insights.- etc.

Über Autor(innen)

Samiksha Shukla is a scholar and educator specializing in data science, cybersecurity, and privacy-preserving technologies. Currently serving as the head and professor in the Department of CSE-Cyber Security, Dayananda Sagar Academy of Technology and Management, Bangalore, she has made significant contributions to advancing data science education and research. Dr. Shukla established the Department of Data Science at Christ University’s Pune Lavasa Campus, demonstrating her leadership in curriculum development and institutional growth. Her research focuses on privacy-preserving data mining, secure multi-party computation, and integrated applications of data science in healthcare and social security. She has authored and edited notable publications, including books on data security, data economy, data ethics, and bio-inspired computational paradigms, and has numerous research articles published in reputed international journals and conferences.

Hiroki Sayama is a professor in the Department of Systems Science and Industrial Engineering and the director of the Center for Collective Dynamics of Complex Systems (CoCo) at Binghamton University, State University of New York, USA. He also serves as a non-tenured professor in the School of Commerce at Waseda University, Japan, as well as an external faculty member of the Vermont Complex Systems Center at the University of Vermont. He received his B.Sc., M.Sc., and D.Sc. in Information Science, all from the University of Tokyo, Japan. He did his postdoctoral work at the New England Complex Systems Institute in Cambridge, Massachusetts. His research interests include complex dynamical networks, human and social dynamics, collective behaviors, artificial life/chemistry, interactive systems, and complex systems education, among others.

Kapil Tiwari is a distinguished senior manager of Software Development at Amazon with over 20 years of extensive experience in AI, big data, and privacy-preserving machine learning. Holding a Ph.D. in Computer Science, he specializes in developing innovative solutions that integrate ethical considerations with cutting-edge technology. His research contributions include multiple patents, influential publications, and books on data ethics and the digital economy, positioning him as a thought leader in the field.

Jossy Paul George is a researcher and academic leader in Computer Science and Human Resources. With a doctoral degree in computer science from Christ University, Bengaluru, his research primarily focuses on biometric recognition algorithms, including fingerprint and face recognition, with the aim of enhancing accuracy and efficiency in biometric systems. He has authored 100 Scopus-indexed publications in reputable international and national journals, contributing significantly to image processing, biometrics, and artificial intelligence.

Joseph Varghese Kureethara is a mathematician and academic leader with expertise in graph theory, optimization, and social networks. Currently serving as the head of the Department of Mathematics at Kuriakose Elias College, Mannanam, India, he has also held positions such as a treasurer of the Academy of Discrete Mathematics and Applications and director of the Centre for Research at Christ University. With a Ph.D. in Mathematics from Manonmaniam Sundaranar University, he has made significant contributions through research and publications across data science, education, and network theory. His scholarly works include books on data security, pedagogical innovations, and graph-theoretic concepts, as well as numerous journal articles and conference proceedings.