Karabayev N 1

1. Graph-Based Methodology for Security Risk Assessment in Wireless IoT Networks
2. A Traffic Analysis and Node Categorization- Aware Machine Learning-Integrated Framework for Cybersecurity Intrusion Detection and Prevention of WSNs in Smart Grids
3. An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT
4. An Impact-Aware and Taxonomy-Driven Explainable Machine Learning Framework with Edge Computing for Security in Industrial IoT–Cyber Physical Systems
5. Comprehensive Study on Detecting Multi-Class Classification of IoT Attack Using Machine Learning Methods
6. Cybersecurity Solutions for Industrial Internet of Things–Edge Computing Integration: Challenges, Threats, and Future Directions
7. Methodology for Detection and Identification of Wormhole Attacks in Wireless Sensor Networks for Cyber-Physical Systems
8. Network Attack Detection Using NeuroEvolution of Augmenting Topologies (NEAT) Algorithm
9. Penetration Testing and Machine Learning-Driven Cybersecurity Framework for IoT and Smart City Wireless Networks
10. Towards robust security in WSN: a comprehensive analytical review and future research directions
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