BioEnvsense:关键基础设施可用的网络安全框架

Farnaz Farid
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引用次数: 0

摘要

网络安全解决方案需要多学科的方法,因为大约95%的网络安全事件源于行为问题。内部威胁是一个重大问题,90%的企业报告遇到过此类威胁。已经提出了基于行为的解决方案来处理非故意的内部威胁,其中包括及时通知和有效的培训材料。人脸识别和指纹等基于生物特征的解决方案也被提出,以尽量减少此类威胁。然而,仍然需要新的方法来引入系统控制,以处理不可预测的用户行为和状态,以减轻此类恶意网络安全事件。这项工作提出了一个概念框架,用于使用软生物识别技术和使用传感器的上下文工作条件来确定用户的情绪状态,以最大限度地减少基于非故意行为的恶意网络事件。该框架将测量用户的精神和情绪状态以及环境条件,并在必要时采取额外的预防措施,例如提供指示、备份或限制访问。总体而言,所提议的框架提供了一个可用的基于上下文和生物识别的网络安全解决方案,可以显着提高系统和用户的安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BioEnvsense: A Usable Cybersecurity Framework for Critical Infrastructure
Cybersecurity solutions require a multidisciplinary approach, as around 95% of cybersecurity incidents stem from behavioral issues. Insider threats are a significant concern, with 90% of enterprises reporting experiencing such threats. Behavioral-based solutions have been proposed to deal with non-intentional insider threats, which include timely notifications and effective training materials. Biometric-based solutions such as face recognition and fingerprints have also been proposed to minimize such threats. However, there is still a need for new approaches to introduce controls on systems to deal with unpredictable user behavior and states to mitigate such malicious cybersecurity incidents. This work proposes a conceptual framework for determining the emotional states of users using soft biometrics and contextual working conditions using sensors to minimize non-intentional behavioral-based malicious cyber incidents. The framework will measure users' mental and emotional states and environmental conditions and take extra precautions when necessary, such as providing instructions, backups or limiting access. Overall, the proposed framework offers a usable contextual and biometric-based cybersecurity solution that could significantly improve the security of systems and users alike.
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