A Survey on Network Security-Related Data Collection Technologies

Loading...
Thumbnail Image
Journal Title
Journal ISSN
Volume Title
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
Date
2018
Major/Subject
Mcode
Degree programme
Language
en
Pages
21
18345-18365
Series
IEEE Access, Volume 6
Abstract
Security threats and economic loss caused by network attacks, intrusions and vulnerabilities have motivated intensive studies on network security. Normally, data collected in a network system can reflect or can be used to detect security threats. We define these data as network security-related data. Studying and analyzing security-related data can help detect network attacks and intrusions, thus making it possible to further measure the security level of the whole network system. Obviously, the first step in detecting network attacks and intrusions is to collect security-related data. However, in the context of big data and 5G, there exist a number of challenges in collecting these security-related data. In this paper, we first briefly introduce network security-related data, including its definition and characteristics, and the applications of network data collection. We then provide the requirements and objectives for security-related data collection and present a taxonomy of data collection technologies. Moreover, we review existing collection nodes, collection tools and collection mechanisms in terms of network data collection and analyze them based on the proposed requirements and objectives towards high quality security-related data collection. Finally, we discuss open research issues and conclude with suggestions for future research directions.
Description
Keywords
Communication networks, Data collection, data collection technologies, Intrusion detection, large-scale heterogeneous networks, Malware, Monitoring, network security, security-related data, Telecommunication traffic
Other note
Citation
Lin, H, Yan, Z, Chen, Y & Zhang, L 2018, ' A Survey on Network Security-Related Data Collection Technologies ', IEEE Access, vol. 6, no. 1, pp. 18345-18365 . https://doi.org/10.1109/ACCESS.2018.2817921