基于深度学习神经网络的窄目标安全网络中动态MAC地址的客户端识别算法

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS
A. Tyutyunnik, E. Lobaneva, A. Lazarev
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引用次数: 0

摘要

现有的网段客户端识别算法是基于MAC地址静态绑定客户端。MAC地址生成基于0-256个字符的伪随机序列。考虑到这一特点,软件是基于使用双向神经网络生成MAC地址的算法开发的,随后集成了一个决策支持系统模块。开发的软件的第二个特性是能够设置MAC有效期超时,这将限制对网段的访问并增加安全系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm for identifying clients based on dynamic MAC addresses in narrowly targeted secure networks using deep learning neural networks
Existing algorithms for identifying clients on a network segment are based on static client binding by MAC address. MAC address generation is based on pseudo-random sequences of 0–256 characters. With this feature in mind, software was developed based on an algorithm for generating MAC addresses using bidirectional neural networks, followed by integration of a decision support system module. A secondary feature of the developed software is the ability to set a MAC validity timeout, which will limit access to the network segment and increase the security factor.
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
27
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