  Recent changes to greenhouse gas emission policies are catalyzing the
electric vehicle (EV) market making it readily accessible to consumers. While
there are challenges that arise with dense deployment of EVs, one of the major
future concerns is cyber security threat. In this paper, cyber security threats
in the form of tampering with EV battery's State of Charge (SOC) was explored.
A Back Propagation (BP) Neural Network (NN) was trained and tested based on
experimental data to estimate SOC of battery under normal operation and
cyber-attack scenarios. NeuralWare software was used to run scenarios.
Different statistic metrics of the predicted values were compared against the
actual values of the specific battery tested to measure the stability and
accuracy of the proposed BP network under different operating conditions. The
results showed that BP NN was able to capture and detect the false entries due
to a cyber-attack on its network.
