A new lightweight method for security risk assessment based on fuzzy cognitive maps

P. Szwed, Pawel Skrzynski
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引用次数: 40

Abstract

Abstract For contemporary software systems, security is considered to be a key quality factor and the analysis of IT security risk becomes an indispensable stage during software deployment. However, performing risk assessment according to methodologies and standards issued for the public sector or large institutions can be too costly and time consuming. Current business practice tends to circumvent risk assessment by defining sets of standard safeguards and applying them to all developed systems. This leads to a substantial gap: threats are not re-evaluated for particular systems and the selection of security functions is not based on risk models. This paper discusses a new lightweight risk assessment method aimed at filling this gap. In this proposal, Fuzzy Cognitive Maps (FCMs) are used to capture dependencies between assets, and FCM-based reasoning is performed to calculate risks. An application of the method is studied using an example of an e-health system providing remote telemonitoring, data storage and teleconsultation services. Lessons learned indicate that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on the effectiveness of the security system.
一种基于模糊认知图的安全风险评估新方法
对于当代软件系统来说,安全性被认为是一个关键的质量因素,IT安全风险分析成为软件部署过程中不可缺少的一个阶段。但是,根据为公共部门或大型机构发布的方法和标准进行风险评估可能过于昂贵和耗时。当前的业务实践倾向于通过定义一组标准保障措施并将其应用于所有已开发的系统来规避风险评估。这导致了一个巨大的差距:没有针对特定系统重新评估威胁,安全功能的选择也不是基于风险模型。本文讨论了一种新的轻量级风险评估方法,旨在填补这一空白。在这个建议中,使用模糊认知图(fcm)来捕获资产之间的依赖关系,并进行基于fcm的推理来计算风险。以提供远程远程监测、数据存储和远程会诊服务的电子卫生系统为例,研究了该方法的应用。经验教训表明,所提出的方法是一种高效和低成本的方法,可以对安全系统的有效性进行即时反馈和推理。
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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