Application Communities Detection in Network
Source abstract
Abstract
The continuous growth of Internet traffic and its applications causes more difficulties for analyzing Internet communications. It has become an increasingly challenging task to discover latent community structure and find abnormal behavior patterns in network communication. In this paper, we propose a new type of network community—the application community—which can help understand large network structure and find anomaly network behavior. To detect such a community, a method is proposed whose first step is aggregating the nodes according to their topological relationships of the communication. It then clusters different application nodes according to the communication behavior modes in the same topological partition. Empirical results show that this method can accurately detect communities of different applications without any prior knowledge. In addition, it can identify the communities more accurately than other methods. Thus, this research greatly benefits the administration of IoT and cyber security.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Complex Network Analysis Techniques · Network Security and Intrusion Detection · Internet Traffic Analysis and Secure E-voting
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
References (29)
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