TY  - EJOU
AU  - Al-E’mari, Salam 
AU  - Sanjalawe, Yousef 
AU  - Allehyani, Budoor 
AU  - Kurdi, Ghader 
AU  - Makhadmeh, Sharif 
AU  - Jaradat, Ameera 
AU  - Hijazi, Duaa 

TI  - Forensic Analysis of Cyberattacks in Electric Vehicle Charging Systems Using Host-Level Data
T2  - Computers, Materials \& Continua

PY  - 2025
VL  - 85
IS  - 2
SN  - 1546-2226

AB  - Electric Vehicle Charging Systems (EVCS) are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet of Things (IoT) environments, raising significant security challenges. Most existing research primarily emphasizes network-level anomaly detection, leaving critical vulnerabilities at the host level underexplored. This study introduces a novel forensic analysis framework leveraging host-level data, including system logs, kernel events, and Hardware Performance Counters (HPC), to detect and analyze sophisticated cyberattacks such as cryptojacking, Denial-of-Service (DoS), and reconnaissance activities targeting EVCS. Using comprehensive forensic analysis and machine learning models, the proposed framework significantly outperforms existing methods, achieving an accuracy of 98.81%. The findings offer insights into distinct behavioral signatures associated with specific cyber threats, enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.
KW  - Electric vehicle charging systems; forensic analysis; cybersecurity; host security; cyber-physical systems

DO  - 10.32604/cmc.2025.067950