Scanning Task Scheduling Strategy in Distributed Vulnerability Detection System

Reasonable scanning task scheduling strategy can improve the scanning efficiency of vulnerability detection systems at a large extent. Task scheduling problem has been proved to be an NP-complete problem. Based on the request and characteristics of vulnerability detection technology, this paper establishes a distributed scanning task scheduling model, and describes a scanning task distributing algorithm. Genetic algorithms (GA) and ant colony algorithm (ACA) have been widely used to solve various types of NP problem. So far, they have been used to research scheduling algorithms, but there are still some defects. In order to overcome the shortcomings, after having studied the suggested algorithms for scanning task scheduling, a new algorithm that combines genetic algorithm and ant colony algorithm is proposed. Compared with the third reference, the algorithm has better load-balancing rate, stability and convergence. The effectiveness of the algorithm is verified by simulation experiment.