Targeted Attacks Detection and Security Intruders Identification in the Cyber Space

Q1 Mathematics
Z. Avkurova, Sergiy Gnatyuk, Bayan Abduraimova, Kaiyrbek Makulov
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引用次数: 0

Abstract

The number of new cybersecurity threats and opportunities is increasing over time, as well as the amount of information that is generated, processed, stored and transmitted using ICTs. Particularly sensitive are the objects of critical infrastructure of the state, which include the mining industry, transport, telecommunications, the banking system, etc. From these positions, the development of systems for detecting attacks and identifying intruders (including the critical infrastructure of the state) is an important and relevant scientific task, which determined the tasks of this article. The paper identifies the main factors influencing the choice of the most effective method for calculating the importance coefficients to increase the objectivity and simplicity of expert assessment of security events in cyberspace. Also, a methodology for conducting an experimental study was developed, in which the goals and objectives of the experiment, input and output parameters, the hypothesis and research criteria, the sufficiency of experimental objects and the sequence of necessary actions were determined. The conducted experimental study confirmed the adequacy of the models proposed in the work, as well as the ability of the method and system created on their basis to detect targeted attacks and identify intruders in cyberspace at an early stage, which is not included in the functionality of modern intrusion detection and prevention systems.
网络空间定向攻击检测和安全入侵者识别
随着时间的推移,新的网络安全威胁和机会越来越多,利用信息和传播技术生成、处理、存储和传输的信息量也越来越大。尤其敏感的是国家关键基础设施的对象,包括采矿业、运输、电信、银行系统等。从这些角度来看,开发检测攻击和识别入侵者(包括国家重要基础设施)的系统是一项重要而相关的科学任务,这也决定了本文的任务。本文确定了影响选择最有效的重要性系数计算方法的主要因素,以提高网络空间安全事件专家评估的客观性和简便性。此外,还制定了开展实验研究的方法,其中确定了实验的目的和目标、输入和输出参数、假设和研究标准、实验对象的充分性以及必要行动的顺序。所进行的实验研究证实了工作中提出的模型的适当性,以及在其基础上创建的方法和系统在早期阶段检测有针对性的攻击和识别网络空间入侵者的能力,这是现代入侵检测和防御系统的功能所不包括的。
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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来源期刊
CiteScore
4.10
自引率
0.00%
发文量
33
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