基于蚁群算法和网络回溯技术的网络异常分析模型构建

Construction of network anomaly analysis model based on ant colonyalgorithm and network backtracking technology

面对网络攻击的复杂化,传统蚁群算法在大网络中易陷入局部最优。为此,此次研究旨在优化网络异常分析技术,通过将蚁群算法与网络回溯技术相结合,实现了对基础算法的优化,并引入软件定义网络的路由策略进行均衡。结果表明,蚁群优化的网络链路利用率在峰值负载时,相较于等价多径路由和最短路径分别高出16.9%和9.8%。网络的吞吐率平均值亦表明蚁群策略在维持路由稳定性上的优越性能。仿真实验中,新策略成功识别了17个潜在攻击路径,其中路径9被认定为主攻击途径。在复杂网络环境下,该算法的效能超过其他方法约38%。可以看出,结合蚁群算法和网络回溯技术的模型在大型网络异常分析中具有显著优势。此研究为网络安全领域提供了更为高效的异常检测与应对手段。

Faced with the complexity of network attacks,traditional ant colony algorithms tend to fall into local optimality in large networks.Therefore,this study aims to optimize the network anomaly analysis technology.By combining ant colony algorithm and network backtracking technology,the basic algorithm is optimized,and the software-defined network routing strategy is introduced to balance.The results show that the link utilization of ant colony optimization is 16.9%and 9.8%higher than that of equivalent multipath routing and shortest path,respectively,at peak load.The average throughput rate of the network also shows that the ant colony strategy has superior performance in maintaining routing stability.In the simulation experiment,the new strategy successfully identified 17 potential attack paths,among which path 9 was identified as the main attack path.In complex network environment,the performance of this algorithm is about 38%higher than other methods.It can be seen that the model combining ant colony algorithm and network backtracking technology has significant advantages in large-scale network anomaly analysis.This research provides a more efficient method for anomaly detection and response in network security field.