AI Based Directory Discovery Attack and Prevention of the Medical Systems

Ying He, Cunjin Luo, Jiyuan Zheng, Kuanquan Wang, Heng-Di Zhang
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引用次数: 1

Abstract

The medical system has been targeted by the cyber attackers, who aim to bring down the health security critical infrastructure. This research is motivated by the recent cyber-attacks happened during COVID 19 pandemics which resulted in the compromise of the diagnosis results. This study was carried to demonstrate how the medical systems can be penetrated using AI-based Directory Discovery Attack and present security solutions to counteract such attacks. We then followed the NIST (National Institute of Standards and Technology) ethical hacking methodology to launch the AI-based Directory Discovery Attack. We were able to successfully penetrate the system and gain access to the core of the medical directories. We then proposed a series of security solutions to prevent such cyber-attacks.
基于AI的医疗系统目录发现攻击及预防
医疗系统已经成为网络攻击者的目标,他们的目标是摧毁医疗安全的关键基础设施。此次研究的动机是,最近在新冠肺炎大流行期间发生的网络攻击导致了诊断结果的泄露。本研究旨在展示如何使用基于人工智能的目录发现攻击渗透医疗系统,并提供安全解决方案来对抗此类攻击。然后,我们遵循NIST(美国国家标准与技术研究所)的道德黑客方法,启动了基于人工智能的目录发现攻击。我们成功地侵入了系统,进入了医疗目录的核心。然后,我们提出了一系列安全解决方案,以防止此类网络攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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