信息共享伙伴关系的安全检查指标。

IF 3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Risk Analysis Pub Date : 2024-07-01 Epub Date: 2024-01-21 DOI:10.1111/risa.14267
Wendy Yu, Zachary A Collier, Shital Thekdi
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引用次数: 0

摘要

最近的历史表明,公司之间共享信息既有好处,也有风险。信息共享有利于实现共同的商业目标。然而,信息共享也会带来与安全相关的问题,可能会使公司面临隐私泄露,对经济、声誉和安全造成重大影响。企业在评估当前和潜在的信息共享伙伴关系时,必须利用现有信息来评估与信息共享相关的安全性。企业的 "细枝末节 "或隐私政策可以为正在考虑建立新的和持续的信息共享合作关系的各类企业提供安全信号。在本文中,我们开发了一种在合作伙伴选择过程中衡量和基准信息安全政策的方法,可帮助指导基于风险的信息共享安全投资。我们开发了一种收集和解释公司隐私政策的方法,通过利用自然语言处理指标和开发基准指标来评估这些政策的特征,并了解这些特征在信息共享合作关系中的相互关系。我们将在 500 家高收入企业中演示该方法。风险管理者、信息安全专业人士以及各行业中达成信息共享协议的个人都会对这一方法和管理见解感兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security screening metrics for information-sharing partnerships.

Recent history has shown both the benefits and risks of information sharing among firms. Information is shared to facilitate mutual business objectives. However, information sharing can also introduce security-related concerns that could expose the firm to a breach of privacy, with significant economic, reputational, and safety implications. It is imperative for organizations to leverage available information to evaluate security related to information sharing when evaluating current and potential information-sharing partnerships. The "fine print" or privacy policies of firms can provide a signal of security across a wide variety of firms being considered for new and continued information-sharing partnerships. In this article, we develop a methodology to gauge and benchmark information security policies in the partner-selection process that can help direct risk-based investments in information sharing security. We develop a methodology to collect and interpret firm privacy policies, evaluate characteristics of those policies by leveraging natural language processing metrics and developing benchmarking metrics, and understand how those characteristics relate to one another in information-sharing partnership situations. We demonstrate the methodology on 500 high-revenue firms. The methodology and managerial insights will be of interest to risk managers, information security professionals, and individuals forming information sharing agreements across industries.

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来源期刊
Risk Analysis
Risk Analysis 数学-数学跨学科应用
CiteScore
7.50
自引率
10.50%
发文量
183
审稿时长
4.2 months
期刊介绍: Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include: • Human health and safety risks • Microbial risks • Engineering • Mathematical modeling • Risk characterization • Risk communication • Risk management and decision-making • Risk perception, acceptability, and ethics • Laws and regulatory policy • Ecological risks.
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