Journal
SENSORS
Volume 22, Issue 22, Pages -Publisher
MDPI
DOI: 10.3390/s22228841
Keywords
data analytics; network management; multiagent system; serendipity; information recommendation; data presentation
Funding
- JSPS KAKENHI [JP22K12143]
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This study proposes a multiagent-based data presentation mechanism for heuristic inference in network management tasks. The results indicate that multifaceted presentation of data can better support administrators compared to selected single-faceted optimal presentation.
Although network management tasks are highly automated using big data and artificial intelligence technologies, when an unforeseen cybersecurity problem or fault scenario occurs, administrators sometimes directly analyze system data to make a heuristic decision. However, a wide variety of information is required to address complex cybersecurity risks, whereas current systems are focused on narrowing the candidates of information. In this study, we propose a multiagent-based data presentation mechanism (MADPM) that consists of agents operating data-processing tools that store and analyze network data. Agents in MADPM interact with other agents to form data-processing sequences. In this process, we design not only the composition of the sequence according to requirements, but also a mechanism to expand it to enable multifaceted analysis that supports heuristic reasoning. We tested five case studies in the prototype system implemented in an experimental network. The results indicated that the multifaceted presentation of data can support administrators more than the selected single-faceted optimal presentation. The final outcome of our proposed approach is the provision of a multifaceted and cross-system data presentation for heuristic inference in network management tasks.
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