首页> 美国卫生研究院文献>other >Characterizing and Measuring Maliciousness for Cybersecurity Risk Assessment
【2h】

Characterizing and Measuring Maliciousness for Cybersecurity Risk Assessment

机译:表征和测量网络安全风险评估的恶意

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Cyber attacks have been increasingly detrimental to networks, systems, and users, and are increasing in number and severity globally. To better predict system vulnerabilities, cybersecurity researchers are developing new and more holistic approaches to characterizing cybersecurity system risk. The process must include characterizing the human factors that contribute to cyber security vulnerabilities and risk. Rationality, expertise, and maliciousness are key human characteristics influencing cyber risk within this context, yet maliciousness is poorly characterized in the literature. There is a clear absence of literature pertaining to human factor maliciousness as it relates to cybersecurity and only limited literature relating to aspects of maliciousness in other disciplinary literatures, such as psychology, sociology, and law. In an attempt to characterize human factors as a contribution to cybersecurity risk, the Cybersecurity Collaborative Research Alliance (CSec-CRA) has developed a Human Factors risk framework. This framework identifies the characteristics of an attacker, user, or defender, all of whom may be adding to or mitigating against cyber risk. The maliciousness literature and the proposed maliciousness assessment metrics are discussed within the context of the Human Factors Framework and Ontology. Maliciousness is defined as the intent to harm. Most maliciousness cyber research to date has focused on detecting malicious software but fails to analyze an individual’s intent to do harm to others by deploying malware or performing malicious attacks. Recent efforts to identify malicious human behavior as it relates to cybersecurity, include analyzing motives driving insider threats as well as user profiling analyses. However, cyber-related maliciousness is neither well-studied nor is it well understood because individuals are not forced to expose their true selves to others while performing malicious attacks. Given the difficulty of interviewing malicious-behaving individuals and the potential untrustworthy nature of their responses, we aim to explore the maliciousness as a human factor through the observable behaviors and attributes of an individual from their actions and interactions with society and networks, but to do so we will need to develop a set of analyzable metrics. The purpose of this paper is twofold: (1) to review human maliciousness-related literature in diverse disciplines (sociology, economics, law, psychology, philosophy, informatics, terrorism, and cybersecurity); and (2) to identify an initial set of proposed assessment metrics and instruments that might be culled from in a future effort to characterize human maliciousness within the cyber realm. The future goal is to integrate these assessment metrics into holistic cybersecurity risk analyses to determine the risk an individual poses to themselves as well as other networks, systems, and/or users.
机译:网络攻击已越来越不利于网络,系统和用户,并且在全球范围内其数量和严重性也在增加。为了更好地预测系统漏洞,网络安全研究人员正在开发新的,更全面的方法来表征网络安全系统风险。该过程必须包括表征导致网络安全漏洞和风险的人为因素。在这种情况下,理性,专业知识和恶意是影响网络风险的关键人类特征,但文献中恶意性的特征很差。显然没有与人为因素恶意有关的文献,因为它与网络安全有关,而在其他学科文献(如心理学,社会学和法律)中,仅有很少的涉及恶意方面的文献。为了将人为因素归因于网络安全风险,网络安全合作研究联盟(CSec-CRA)建立了人为因素风险框架。该框架确定了攻击者,用户或防御者的特征,所有这些特征都可能增加或减轻网络风险。在人为因素框架和本体论的背景下讨论了恶意文献和拟议的恶意评估指标。恶意被定义为伤害意图。迄今为止,大多数恶意网络研究都集中在检测恶意软件上,但未能分析个人通过部署恶意软件或执行恶意攻击对他人造成伤害的意图。识别与网络安全相关的恶意人类行为的最新努力包括分析驱动内部威胁的动机以及用户配置文件分析。但是,与网络相关的恶意行为既未被充分研究,也未被充分理解,因为在进行恶意攻击时不会强迫个人将自己的真实自我暴露给他人。考虑到采访恶意行为个体的困难以及其回应的潜在不信任性质,我们的目的是通过个人的可观察到的行为和属性,从其行为以及与社会和网络的互动中探讨恶意行为是人为因素,但这样做是为了因此我们将需要开发一组可分析的指标。本文的目的是双重的:(1)回顾不同学科(社会学,经济学,法律,心理学,哲学,信息学,恐怖主义和网络安全)中与人类恶意相关的文献; (2)识别最初提出的一组评估指标和工具,这些评估指标和工具可能会在未来的工作中被用来剔除网络领域内人为恶意的特征。未来的目标是将这些评估指标集成到整体网络安全风险分析中,以确定个人以及其他网络,系统和/或用户对其自身构成的风险。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号