Public Plug-in Electric Vehicles + Grid Data: Is a New Cyberattack Vector Viable?

Acharya, Samrat; Dvorkin, Yury; Karri, Ramesh

doi:10.1109/tsg.2020.2994177

Cited by 97 publications

(49 citation statements)

References 29 publications

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“…Non-standard cyber-physical interfaces make EVs and EVCS susceptible to attacks that can damage the EV and EVCS equipments. Furthermore, vulnerabilities in these interfaces make it possible to weaponize EVs to launch large-scale, demand-side cyberattacks on the power grid [16].…”

Section: Gpsmentioning

confidence: 99%

“…As a consequence of the attacks, power grid operators will not be able to cope with them without resorting to massive load shedding. For instance, previous work in [16] revealed a cyber threat using publicly available EV charging and power grid data. This can be exploited by an unsophisticated attacker with minimal capabilities (e.g., foreign and domestic non-state actors).…”

Section: Gpsmentioning

confidence: 99%

“…For example, Fig. 1 shows a electrical transmission network and EVCSs in Manhattan, NY, which was reconstructed using exclusively public sources [16].…”

Section: Gpsmentioning

confidence: 99%

“…For instance, if an EVCS permits an user to inject malware through its universal serial bus (USB) port, the user privilege is elevated to an EVCS operator. Greveler et al [27] Tabrizi et al [28] Kumar et al [29] Wu et al [30] AlMajali et al [31] Raman et al [32] Ustundag et al [33] Karimi et al [34] Soltan et al [35] Huang et al [36] Dvorkin et al [37] Amini et al [38] Acharya et al [16] Rohde [39] Khan et al [40] Morrison [41] B. SMART GRID THREATS 1) SCADA Threats SCADA is a centralized monitoring and control system, which is commonly used in real-world power grids, and can be split into four main components: 1) a central master terminal unit assisted by various control subsystems such as an energy management system, a DER management system, a geographic information system, and a DR automation, 2) a human-machine interface (HMI) for assisting system operators to manage SCADA, 3) field units such as PLC and RTU, and 4) communication channels [42].…”

Section: A Stride Threat Modelmentioning

confidence: 99%

“…The paper provides an in-depth analysis of these threats in the following sections. Additionally, studies [16], [39]- [41] from Table 1, which operationalize EV attacks on the power grid, are also discussed in detail in Section VIII.…”

Section: ) Ev Charging Threatsmentioning

confidence: 99%

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Cybersecurity of Smart Electric Vehicle Charging: A Power Grid Perspective

et al. 2020

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With the roll-out of electric vehicles (EVs), the automobile industry is transitioning away from conventional gasoline-fueled vehicles. As a result, the EV charging demand is continuously growing and to meet this growing demand, various types of electric vehicle charging stations (EVCSs) are being deployed for commercial and residential use. This nexus of EVs, EVCSs, and power grids creates complex cyber-physical interdependencies that can be maliciously exploited to damage each of these components. This paper describes and analyzes cyber vulnerabilities that arise at this nexus and points to the current and emerging gaps in the security of the EV charging ecosystem. These vulnerabilities must be addressed as the number of EVs continue to grow worldwide and their impact on the power grid becomes more viable. The purpose of this paper is to list and characterize all backdoors that can be exploited to seriously harm either EV and EVCS equipments, or power grid, or both. The presented issues and challenges intend to ignite research efforts on cybersecurity of smart EV charging and enhancing power grid resiliency against such demand-side cyberattacks in general. INDEX TERMS Cybersecurity, electric vehicles, electric vehicle charging stations, smart grids.

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Section: Gpsmentioning

confidence: 99%

Section: Gpsmentioning

confidence: 99%

“…For example, Fig. 1 shows a electrical transmission network and EVCSs in Manhattan, NY, which was reconstructed using exclusively public sources [16].…”

Section: Gpsmentioning

confidence: 99%