使用通用安全模板构建信息安全事件教训的实证研究

Ying He, Chris W. Johnson, K. Renaud, Yu Lu, S. Jebriel
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引用次数: 18

摘要

安全事件的数量仍在增加。过去数据泄露事件的再次发生表明,不同的组织并没有有效地吸取教训。这说明了信息安全管理系统(ISMS)中的重要弱点。可以说,公共和私人组织之间的建议共享在学术界和工业界都没有得到足够的重视。例如,关于适当的细节和抽象水平,使不同的组织能够从同一或不同行业的其他公司发生的事件中吸取教训,仍然存在许多问题。提出了通用安全模板,旨在提供一种统一的方式来分享从现实世界的安全事件中吸取的教训。特别地,它采用图形化的目标结构符号(GSN),通过将学到的经验教训映射到ISMS的安全需求,以结构化的方式呈现这些经验教训。在本文中,我们展示了如何使用通用安全模板来构建特定事件的图形概述。我们还展示了可以实例化模板来传达对美国退伍军人事务部数据泄露的调查结果。此外,本文还对这种创建通用安全模板的方法进行了实证评估;这为用户提供了在抽象级别上从安全事件中获得的经验教训的概述,可以帮助在与最初发生攻击的环境不同的未来上下文中实现建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An empirical study on the use of the Generic Security Template for structuring the lessons from information security incidents
The number of security incidents is still increasing. The re-occurrence of past breaches shows that lessons have not been effectively learned across different organisations. This illustrates important weaknesses within information security management systems (ISMS). The sharing of recommendations between public and private organisations has, arguably, not been given enough attention across academic and industry. Many questions remain, for example, about appropriate levels of detail and abstraction that enable different organisations to learn from incidents that occur in other companies within the same or different industries. The Generic Security Template has been proposed, aiming to provide a unified way to share the lessons learned from real world security incidents. In particular, it adapts the graphical Goal Structuring Notation (GSN), to present lessons learned in a structured manner by mapping them to the security requirements of the ISMS. In this paper, we have shown how a Generic Security Template can be used to structure graphical overviews of specific incidents. We have also shown the template can be instantiated to communicate the findings from an investigation into the US VA data breach. Moreover, this paper has empirically evaluated this approach to the creation of a Generic Security Template; this provides users with an overview of the lessons derived from security incidents at a level of abstraction that can help to implement recommendations in future contexts that are different from those in which an attack originally took place.
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