Purpose: Evaluate if automated vulnerability scanning accurately identifies vulnerabilities in computer networks and if this accuracy is contingent on the platforms used.Design/methodology/approach: Both qualitative comparisons of functionality and quantitative comparisons of false positives and false negatives are made for seven different scanners. The quantitative assessment includes data from both authenticated and unauthenticated scans. Experiments were conducted on a computer network of 28 hosts with various operating systems, services and vulnerabilities. This network was set up by a team of security researchers and professionals. Findings:The data collected in this study show that authenticated vulnerability scanning is usable. However, automated scanning is not able to accurately identify all vulnerabilities present in computer networks. Also, scans of hosts running Windows are more accurate than scans of hosts running Linux. Research limitations/implications:This paper focuses on the direct output of automated scans with respect to the vulnerabilities they identify. Areas such as how to interpret the results assessed by each scanner (e.g. regarding remediation guidelines) or aggregating information about individual vulnerabilities into risk measures are out of scope. Practical implications:This paper describes how well automated vulnerability scanners perform when it comes to identifying security issues in a network. The findings suggest that a vulnerability scanner is a useable tool to have in your security toolbox given that user credentials are available for the hosts in your network. Manual effort is however needed to complement automated scanning in order to get satisfactory accuracy regarding network security problems. Originality/value: Previous studies have focused on the qualitative aspects on vulnerability assessment. This study presents a quantitative evaluation of seven of the most popular vulnerability scanners available on the market.
Cyber security research is quintessential to secure computerized systems against cyber threats. Likewise, cyber security training and exercises are instrumental in ensuring that the professionals protecting the systems have the right set of skills to do the job. Cyber ranges provide platforms for testing, experimentation and training, but developing and executing experiments and training sessions are labour intensive and require highly skilled personnel. Several cyber range operators are developing automated tools to speed up the creation of emulated environments and scenarios as well as to increase the number and quality of the executed events. In this paper we investigate automated tools used in cyber ranges and research initiatives designated to augment cyber ranges automation. We also investigate the automation features in CRATE (Cyber Range And Training Environment) operated by the Swedish Defence Research Agency (FOI).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.