HoneyTwin:利用支持机器学习的 SDN 边缘和基于云的蜜罐确保智慧城市安全

IF 3.4 3区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Mohammed M. Alani
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引用次数: 0

摘要

6G 网络有望实现更高的吞吐量和更短的响应时间,为智慧城市的发展提供了重要的推动力。在智慧城市背景下,人们对联网设备的依赖性迅速增加,这促使恶意行为者瞄准这些设备,以实现各种恶意目标。在本文中,我们提出了一种新颖的防御技术,它创建了一个基于云的虚拟化蜜罐/双核,旨在通过基于边缘机器学习的检测系统接收恶意流量。所提出的系统可在软件定义网络支持的边缘路由点中对恶意流量进行早期识别,从而将这些流量从支持 6G 的智慧城市终端分流出去。对拟议系统的测试表明,其准确率超过 99.8%,F1 得分为 0.9984。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HoneyTwin: Securing smart cities with machine learning-enabled SDN edge and cloud-based honeypots

With the promise of higher throughput, and better response times, 6G networks provide a significant enabler for smart cities to evolve. The rapidly-growing reliance on connected devices within the smart city context encourages malicious actors to target these devices to achieve various malicious goals. In this paper, we present a novel defense technique that creates a cloud-based virtualized honeypot/twin that is designed to receive malicious traffic through edge-based machine learning-enabled detection system. The proposed system performs early identification of malicious traffic in a software defined network-enabled edge routing point to divert that traffic away from the 6G-enabled smart city endpoints. Testing of the proposed system showed an accuracy exceeding 99.8%, with an F1 score of 0.9984.

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来源期刊
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing 工程技术-计算机:理论方法
CiteScore
10.30
自引率
2.60%
发文量
172
审稿时长
12 months
期刊介绍: This international journal is directed to researchers, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing. The Journal of Parallel and Distributed Computing publishes original research papers and timely review articles on the theory, design, evaluation, and use of parallel and/or distributed computing systems. The journal also features special issues on these topics; again covering the full range from the design to the use of our targeted systems.
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