Analysis of digital footprints associated with cybersecurity behavior patterns of users of University Information and Education Systems

IF 0.5 Q4 TELECOMMUNICATIONS
V. Lakhno, Nurgazy Kurbaiyazov, Miroslav Lakhno, Olena Kryvoruchko, A. Desiatko, Svitlana Tsiutsiura, Mykola Tsiutsiura
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引用次数: 0

Abstract

The analysis of digital footprints (DF) related to the cybersecurity (cyber risk) user behavior of university information and education systems (UIES) involves the study and evaluation of various aspects of activity in the systems. In particular, such analysis includes the study of typical patterns (patterns) of access to UIES, password usage, network activity, compliance with security policies, identification of anomalous behavior, and more. It is shown that user behavior in UIES is represented by sequences of actions and can be analyzed using the sequential analysis method. Such analysis will allow information security (IS) systems of UIES to efficiently process categorical data associated with sequential patterns of user actions. It is shown that analyzing sequential patterns of cyberthreatening user behavior will allow UIES IS systems to identify more complex threats that may be hidden in chains of actions, not just individual events. This will allow for more effective identification of potential threats and prevention of security incidents in the UIES.
分析与大学信息和教育系统用户网络安全行为模式相关的数字足迹
与大学信息和教育系统(UIES)的网络安全(网络风险)用户行为有关的数字足迹(DF)分析涉及对系统中各方面活动的研究和评估。具体而言,此类分析包括研究访问大学信息和教育系统的典型模式(模式)、密码使用、网络活动、安全策略的遵守情况、异常行为的识别等。研究表明,用户在 UIES 中的行为是由操作序列表示的,可以使用序列分析方法进行分析。这种分析方法可使 UIES 的信息安全(IS)系统有效处理与用户行为序列模式相关的分类数据。分析表明,对具有网络威胁的用户行为的连续模式进行分析,可使 UIES IS 系统识别可能隐藏在行为链(而不仅仅是单个事件)中的更复杂的威胁。这样就能更有效地识别潜在威胁,防止用户和信息服务系统发生安全事件。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
0
审稿时长
12 weeks
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