Abstract:

In modern digital networked industrial control systems, data conflicts and DDoS attacks pose significant threats to system security and stability. Optimization of data conflict and DDoS attack defense mechanisms in industrial control systems based on greedy algorithm was proposed to address these issues synergistically. Firstly, an adaptive resource allocation model was designed based on the greedy algorithm, dynamically adjusting priority allocation strategies by monitoring network traffic and system states in real time, preventing data conflicts and mitigating DDoS attacks effectively. Secondly, controller and observer were developed using the Lyapunov theorem to enhance the system’s ability to handle data conflicts and DDoS attacks. Experimental results show that the proposed method significantly reduces the frequency of data conflicts and improve the system’s resilience to DDoS attacks. Additionally, the effectiveness of the method is validated through simulations of inverted pendulum drones. This research provides a novel solution for the security protection of digital networked industrial control systems.

Key words: digital network industrial control systems, data conflicts, DDoS attacks, greedy algorithm, adaptive resource allocation