A Fuzz Testing Method for Smart Grid Terminals Based on the Isolation Forest Algorithm

With the rapid development of smart grid infrastructure, the proliferation of networked and intelligent devices in power systems has introduced significant cybersecurity challenges. Traditional security approaches, while essential, focus primarily on perimeter defenses and are limited in detecting vulnerabilities within firmware. This paper presents a fuzz testing method enhanced by the Isolation Forest algorithm, designed specifically for identifying security vulnerabilities in smart grid terminal firmware. By combining real-time monitoring, encrypted data transmission, and adaptive feedback, the proposed method provides robust anomaly detection and dynamic test case generation. Experimental results indicate that this approach significantly improves detection accuracy and efficiency, demonstrating its suitability for the rigorous security demands of smart grid environments.