Cybersecurity, IoT, Data Science and Digital Forensics
Description
This book constitutes the refereed proceedings of the first International Conference on Cybersecurity, IoT, Data Science and Digital Forensics, CIDDF 2025, held in The Woodlands, Texas, USA, during October 2-4, 2025.
The 13 full papers and one short paper included in this book were carefully reviewed and selected from 29 submissions. These papers focused on topics such as digital forensics and security analytics; the use of data science, machine learning, and visualization for security and forensic analysis; multimodal AI and intelligent systems; and IoT and system security.
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Content
Performance Evaluation on Widely Used Digital Forensic Tools in Kali Linux.- Hybrid Detection of Command and Control Communications Using Flow-Based Features from Real-World Network Traffic.- Immersive Virtual Reality (VR) in Crime Scene Analysis & Investigation: A Systematic Review: Systematic Review of VR in Crime Scene Investigation.- Evaluating Forensic Techniques for Detecting and Investigating Insider Threats Leveraging Legitimate Access to Systems and Data.- Dynamic Analysis of Malware Detection Using Customized Payloads in Web Applications: Examining The Effectiveness of Manual and Automated Approaches.- System Settings and Security in IoT Devices Using Snort and Suricata.- Generative Reasoning Meets Multimodal Evaluation: A Novel Approach to Activity and Package Diagram Comparison in UML Modeling.- A Real-Time Vietnamese Sign Language Recognition System Using a Lightweight LSTM Model and Hand Key Point Extraction.- IntelliChart: Advanced LangGraph Analytics Platform with AI Workflow Processing and Intelligent Data Insights.-Bilingual Code-Switching Voice Separation with MossFormer2 for Vietnamese-English Mixtures.-Weighted Silhouette Ranking of PCA Projections in Intrusion Detection.- PowerMap and Time-Indexed PCA Trajectories: Interactive Visual Forensics for HPC Incidents.-AI-Powered Phishing Forensics: Detecting and Analyzing Social Engineering Attacks Using Machine Learning.- Advancing Lip-speech Synchronization and Facial Recognition.