EXPLORATION OF COMPUTER NETWORK BY VULNERABILITY SCANNER NESSUS

扫描仪 脆弱性(计算) 计算机科学 漏洞管理 计算机安全 脆弱性评估 网络安全 局域网 计算机网络 人工智能 心理学 心理弹性 心理治疗师
作者
V. Balatska,M. Shabatura
出处
期刊:Vìsnik Lʹvìvsʹkogo deržavnogo unìversitetu bezpeki žittêdìâlʹnostì [Lviv State University of Life Safety]
卷期号:20: 6-11
标识
DOI:10.32447/20784643.20.2019.01
摘要

For today, computer networks are an integral part of our daily lives. As the analysis shows, the network is ex-tremely vulnerable, it can serve as a place of information leakage, changes of configuration of settings and modification of data by the attackers. There are many more threats, and the security of the network requires a great deal of attention to ensure the security of the network in order to maintain the confidentiality and integrity of the data. Organizations must regularly assess the vulnerability of the entire network to test the security level and strengthen the network. We use vulnerability scanners to find weaknesses, which are useful for detecting security vulnerabilities on a case-by-case basis and across the network as a whole. The purpose of the work is to explore the computer network for vulnerabilities using the Nessus Professional scanner. Research Methods – network scanning by Nessus Professional vulnerability scanner. The Nessus Professional vulnerability scanner from Tenable Network Security, which is freely available, was used for the research. The Nessus Professional scanner has been found to have better functionality and performance than other available scanners. The only downside to the scanner is its cost per year, as well as scanning a large number of hosts on the network at a time (over 100 hosts). After the scanner was successfully installed, carried out it was in-spected from the moment it was launched to the generation of host test reports. For the work, the Lviv State University of Life Safety network was tested. In the post-scan report, which is displayed in HTML format, you can see scan details for each host; the number and nature of vulnerabilities; the error correction dashboard. According to the results of testing, vulnerabilities of low, medium and high levels of hazards were identified, totaling 376. Vulnerabilities were ana-lyzed based on the obtained results, namely: a brief description and a way to solve the problem.

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