AI-powered cybersecurity innovations for protecting U.S. critical infrastructure

The critical infrastructure sectors, such as the energy, transportation, healthcare, and communications sectors, are now exposed to sophisticated cyber-attacks that are the result of increased connectivity and complexities associated with the use of technology. The recent cyber-attacks that involved ransomware, advanced persistent threats, and zero-day exploits are testimony to the inadequacies associated with the use of conventional mechanisms used to secure critical systems. This is primarily due to the lack of adaptability and the ability to provide real-time intelligence that conventional mechanisms do not possess. Artificial Intelligence (AI), as an advanced form of cybersecurity, has been increasingly recognized for its ability to support threat detection and response. The present paper intends to identify the deficiencies in existing cybersecurity solutions and present an advanced cybersecurity framework using artificial intelligence for protecting the critical infrastructure in the United States. The cybersecurity framework combines machine learning for anomaly detection and deep learning for threat classification and automated responses for effective cybersecurity. Contributions of this paper include: (i) a study of the state of cyber threats against critical infrastructure in the United States of America, (ii) a systematic investigation of available AI technologies that can safeguard critical infrastructure, and (iii) developing a cybersecurity system that uses AI capable of detecting and forecasting cyber threats in real time. This system shows how AI can greatly improve critical infrastructure cybersecurity systems.