自适应神经网络在网络攻击预测中的软件应用  

Application of Adaptive Neural Networks in Network Attack Prediction

作　　者：王裔楠 WANG Yinan(Guizhou Vocational College of Industry&Commerce,Guiyang Guizhou 551400)

机构地区：[1]贵州工商职业学院,贵州贵阳551400

出　　处：《软件》2025年第3期135-137,共3页Software

摘　　要：随着互联网技术的迅猛发展,网络攻击成为一个严重的安全威胁。传统的防护措施往往难以应对新型攻击手段,因此需要更为先进的预测技术。本文提出了一种基于自适应神经网络的网络攻击预测系统,通过优化模型结构和数据处理流程,提高预测准确性和实时响应能力。本文研究表明,自适应神经网络,尤其是RNN,在网络攻击预测中具有显著优势,可以有效提升网络安全防护水平。With the rapid advancement of internet technology,network attacks have become a significant security threat.Traditional defense measures often struggle to cope with new attack methods,necessitating more advanced predictive techniques.This paper proposes a network attack prediction system based on adaptive neural networks,aimed at improving prediction accuracy and real-time response capabilities through optimized model structure and data processing.The study demonstrates that adaptive neural networks,particularly RNNs,offer significant advantages in network attack prediction and can effectively enhance network security.

关 键 词：自适应神经网络 网络攻击预测 循环神经网络(RNN) 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]