Title
Adaptive security-related data collection with context awareness.
Abstract
The huge economic loss resulting from network attacks and intrusions has led to an intensive study on network security. The network security is usually reflected by some relevant data that can be collected in a network system. By learning and analyzing such data, which are called security-related data, we can detect the intrusions to the network system and further measure its security level. Clearly, the first step of detecting network intrusions is to collect security-related data. However, in the context of 5G and big data, there are a number of challenges in collecting these data due to the heterogeneity of network and ever-growing amount of data. Therefore, traditional data collection methods cannot be applied in the next generation network systems directly, especially for security-related data. This paper presents the design and implementation of an adaptive security-related data collector based on network context in heterogeneous networks. The proposed collector solves the issue of heterogeneity of network system by designing a Security-related Data Description Language (SDDL) to instruct security related data collection in various networking contexts. It also applies adaptive sampling algorithms to reduce the amount of collected data. Furthermore, performance evaluation based on a prototype implementation shows the effectiveness of the adaptive security-related data collector in terms of a number of pre-defined design requirements.
Year
DOI
Venue
2019
10.1016/j.jnca.2018.11.002
Journal of Network and Computer Applications
Keywords
Field
DocType
Security-related data,Adaptive data collection,Heterogeneous network,Network context
Data collection,Next-generation network,Adaptive security,Computer science,Adaptive sampling,Network security,Context awareness,Heterogeneous network,Big data,Distributed computing
Journal
Volume
ISSN
Citations 
126
1084-8045
1
PageRank 
References 
Authors
0.35
21
3
Name
Order
Citations
PageRank
Huaqing Lin171.44
Zheng Yan219928.32
Yulong Fu342.41