Intrusion-Detection-Systems:这是研究论文“为网络安全中的网络入侵检测系统评估浅层和深层神经网络”的回购-源码

上传者: 42104947 | 上传时间: 2021-09-09 16:33:32 | 文件大小: 18.32MB | 文件类型: ZIP
入侵检测系统 此回购协议包含研究论文“”的所有代码和数据集。 抽象的 : 由于在当今世界对网络安全的强烈要求,入侵检测系统(IDS)已成为所有最新ICT系统中的必不可少的层。 IDS要求发现深度神经网络(DNN)的集成,包括发现攻击类型的不确定性和高级网络攻击的复杂性等原因。 在本文中,DNN已被用来预测对网络入侵检测系统(N-IDS)的攻击。 应用具有0.1的学习率的DNN并运行1000个纪元,并且KDDCup-'99'数据集已用于训练和对网络进行基准测试。 为了进行比较,该训练是在同一数据集上与其他几种经典机器学习算法一起完成的,并且DNN的范围为1到5。比较结果并得出结论,3层DNN具有优于其他所有经典机器的性能。学习算法。 关键字: 入侵检测,深度神经网络,机器学习,深度学习 编者: ** , † , †和 ‡ ∗印度Amrita Vishwa Vidyapeeth

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