通信网络大规模数据流隐蔽攻击轻量级检测算法  

A Lightweight Detection Algorithm for Covert Attacks in Large-Scale Data Flows of Communication Networks

作　　者：祁巧云 QI Qiaoyun(School of Artificial Intelligence and Information Engineering,Jinken College of Technology,Nanjing 211156,China)

机构地区：[1]金肯职业技术学院人工智能与信息工程学院,南京211156

出　　处：《微处理机》2025年第1期33-37,共5页Microprocessors

基　　金：江苏高校哲学社会科学研究项目“基于教师能力提升与学生自主学习的数字化资源库的创新研究——以计算机类课程为例”(2023SJYB0859)。

摘　　要：针对通信网络中低频率、随机化等隐蔽攻击难以检测且现有方法效率低下的问题,设计了一种大规模数据流隐蔽攻击检测算法。该算法通过挖掘能量消耗特征和计算参数差异系数,避免循环迭代过程,构建轻量级检测模型,并优化数据包转发监听机制。实验结果表明,该算法可在1秒内完成隐蔽攻击检测,3秒内恢复通信信号,可扩展性超过93%。研究成果为提高通信网络安全性提供了新的技术方案,具有良好的应用价值。To address the challenge of detecting low-frequency and randomized covert attacks in com-munication networks and the inefficiency of existing methods,this paper designs a detection algorithm for large-scale data flow covert attacks.The algorithm avoids iterative processes by mining energy consumption features and calculating parameter variation coefficients,constructing a lightweight detection model with optimized packet forwarding monitoring mechanism.Experimental results show that the algorithm can detect covert attacks within 1 second,restore communication signals within 3 seconds,and achieve over 93%scalability.The research provides a new technical solution for enhancing communication network security and demonstrates good application value.

关 键 词：通信网络 大规模数据流 隐蔽攻击 信任值 轻量级 优化数据 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]