Biblio

This paper focuses on the secure integration of distributed energy resources (DERs), especially pluggable electric vehicles (EVs), with the power grid. We consider the vehicle-to-grid (V2G) system where EVs are connected to the power grid through an `aggregator' In this paper, we propose a novel Cyber-Physical Anomaly Detection Engine that monitors system behavior and detects anomalies almost instantaneously (worst case inspection time for a packet is 0.165 seconds1). This detection engine ensures that the critical power grid component (viz., aggregator) remains secure by monitoring (a) cyber messages for various state changes and data constraints along with (b) power data on the V2G cyber network using power measurements from sensors on the physical/power distribution network. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the protocol messages to enhance the safety of the aggregator. To the best of our knowledge, this is the first piece of work that combines (a) the EV charging/discharging protocols, the (b) cyber network and (c) power measurements from physical network to detect intrusions in the EV to power grid system.1Minimum latency on V2G network is 2 seconds.

Side Channel Attacks (SCA) using power measurements are a known method of breaking cryptographic algorithms such as AES. Published research into attacks on AES frequently target only AES-128, and often target only the core Electronic Code-Book (ECB) algorithm, without discussing surrounding issues such as triggering, along with breaking the initialization vector. This paper demonstrates a complete attack on a secure bootloader, where the firmware files have been encrypted with AES-256-CBC. A classic Correlation Power Analysis (CPA) attack is performed on AES-256 to recover the complete 32-byte key, and a CPA attack is also used to attempt recovery of the initialization vector (IV).