DCA: Delayed Charging Attack on the Electric Shared Mobility System

• DOI: 10.48550/arxiv.2302.01972
• Publication Date: 2023-01-01
• Authors: Shuocheng Guo; Hanlin Chen; Mizanur Rahman; Xinwu Qian
• Keywords: FOS: Computer and information sciences; Physics - Physics and Society; Computer Science - Cryptography and Security; 05 social sciences; FOS: Physical sciences; 02 engineering and technology; Systems and Control (eess.SY); Dynamical Systems (math.DS); Physics and Society (physics.soc-ph); Electrical Engineering and Systems Science - Systems and Control; Optimization and Control (math.OC); 0502 economics and business; 0202 electrical engineering, electronic engineering, information engineering; FOS: Electrical engineering, electronic engineering, information engineering; FOS: Mathematics; Mathematics - Dynamical Systems; Mathematics - Optimization and Control; Cryptography and Security (cs.CR)

An efficient operation of the electric shared mobility system (ESMS) relies heavily on seamless interconnections among vehicles (SEV), vehicle supply equipment (EVSE), and grid. Nevertheless, this interconnectivity also makes ESMS vulnerable to cyberattacks that may cause short-term breakdowns or long-term degradation ESMS. This study focuses one such attack with long-lasting effects, Delayed Charge Attack (DCA), stealthily delays charging service by exploiting physical communication vulnerabilities. To begin, we present threat model highlighting assets, information flow, access points. We next identify a linked sequence vulnerabilities as viable vector for launching DCA. Then, detail implementation DCA, which can effectively bypass detection in SEV's battery management cross-verification cloud environment. test DCA against various Anomaly Detection (AD) algorithms simulating dynamics Susceptible-Infectious-Removed-Susceptible process, where EVSE be compromised detected repair. Using real-world taxi trip data locations New York City, allows us explore impacts validate consequences. The results show 10-min delay 12-min longer queuing times 8% more unfulfilled requests, leading 10.7% (\$311.7) weekly revenue loss per driver. With AD algorithms, remains at least 3.8% (\$111.8) increased repair costs \$36,000, suggesting DCA's robustness AD.