Optimizing V2G Dynamics: An AI-Enhanced Secure Protocol for Energy Management in Industrial Cyber-Physical Systems
Shafiq Ahmed, Mohammad Hossein Anisi
Abstract
The rapid advancement of intelligent transportation systems and the growing demand for sustainable energy solutions have elevated the Vehicle-to-Grid (V2G) paradigm in Industrial Cyber-Physical Systems (ICPS). This paper presents an AI-Enhanced Secure Protocol for V2G Energy Management, integrating Artificial Intelligence (AI) through Long Short-Term Memory (LSTM) networks with advanced cryptographic techniques for optimizing energy distribution between smart grids and electric vehicles. This protocol enhances system security and device integrity, effectively countering cyber threats and physical tampering. Emphasizing practical applicability, it demonstrates scalability and versatility across various smart grid environments, marking a significant step in AI-integrated cybersecurity for sustainable energy management. Comparative analysis reveals reductions in computation and communication costs by 49.79% and 23.24%, respectively, highlighting the efficiency of the protocol and its potential to enhance smart grid security frameworks.