Cybersecurity and Artificial Intelligence Strategies

This book constitutes the post-conference proceedings of the Second International Conference on Cybersecurity and Artificial Intelligence Strategies, CAIS 2025 held in Baghdad, Iraq during September 17-18, 2025.

The 23 full papers included in this book were carefully reviewed and selected from 101 submissions. The papers are organized in these topical sections: Security and Privacy; Applied Computing and Computing Methodologies.

Inhalt

.- Security and Privacy.
.- An Improved DBSCAN Clustering Algorithm for Bot Detection on Twitter.
.- Anomaly Detection in Blockchain Transactions Using Supervised Machine Learning.
.- Artificial Intelligence Strategies for Advancing Cybersecurity and Intrusion Detection Systems (IDs).
.- BERT-Enhanced Dual-Attention RNN for Short Text Spam Detection.
.- Effective Knowledge Graph Representation for Cybersecurity Using AI-Based X Data and Named Entity Relation Technique .
.- Enhancement of Cybersecurity in AI Services Using Hybrid Homomorphic Encryption.
.- Innovative Neural Network Architecture for Progressive Windows Malware Detection via Adaptive Feature Fusion and Multi-Stage Learning .
.- LiteStegNet: A Lightweight Deep Learning Framework for Video Steganography in IoT-Based Systems.
.- Secure and Workload-Aware Virtual Machine Migration: Enhancing Performance, Energy Efficiency, and Cyber Resilience in Cloud Data Centres.
.- AI-Powered Malware Analysis in Military Cybersecurity: A Deep Learning Approach.
.- Applied Computing.
.- A Modern Software Engineering Approach to UML Class Diagram Evaluation.
.- Advancement in E-marketing Strategy using Support Vector Machine and Apriori Algorithm.
.- Advancing Real-Time Facial Expression Recognition: A Deep Learning-Based Video Stream Analysis.
.- An Enhanced Deep Learning Approach for Writer Identification and Verification Using Corner Detection.
.- Deep Learning Techniques for Predicting Transcription Factor Binding Sites (TFBSs) from DNA Sequencing Data.
.- Dual-Phase Sensor Deployment Using Pelican Optimization Algorithm: A Case Study on Air Pollution Monitoring Baghdad City.
.- Hand Gesture Classification on Custom Abductees-Rescue Dataset using an Optimized LSTM.
.- WLDRD: Dynamic Weighted Load Balancing with Adaptive Request Distribution in Distributed Systems.
.- Computing Methodologies.
.- Design and Implementation of a Handshaking Algorithm for Enhanced Protection of High-Tension Towers in Iraq.
.- DiploNet: A Deep Learning Semantic Segmentation Model for Glaucoma Diagnosis.
.- Summarizing Research Papers with Transformer Models.
.- LESS is more: Guiding LLMs for Formal Requirement and Test Case Generation.
.- Traffic equilibria prediction using inverse reinforcement learning.