A Comprehensive Survey of Hardware Security for Artificial Intelligence Systems: Threats, Countermeasures, And Future Directions

Abstract

The artificial intelligence's rapid expansion and dependence on specialized hardware accelerators have caused security issues beyond software flaws. The global AI hardware industry is expected to exceed $250 billion by 2028. This expansion coincides with a troubling rise in hardware security incidents, estimated to rise by almost 300% between 2022 and 2025. This study thoroughly analyzes AI hardware security concerns, countermeasures, and research opportunities. Hardware-based assaults fall into three categories: model extraction, manipulation, and service interruption. Hardware Trojans, side-channel analysis, and fault injection are vectors. These can degrade model performance, steal proprietary architectures, or misclassify targets. Real-world evidence shows that stealthy Trojans can degrade the accuracy of deep neural networks by over 50% without being detected, whereas side-channel approaches can retrieve nearly all parameters accurately. Modern countermeasures like hardware-based trusted execution environments, runtime monitoring, formal verification, and anomaly detection are also examined. It discusses their merits and downsides, economic impact, and performance. Market research system reliability. Finally, we discuss emerging research issues, including concerns about the quantum era, vulnerabilities in the semiconductor supply chain, and flaws in edge AI devices.