Abstract
Network Security Situation Awareness (NSSA) is a security theory which can perceive the network threat from a global perspective. In this paper, we present a Cognitive Awareness-Control Model (CACM) for NSSA. CACM adopts the cross-layer architecture and cognitive circle which can break through the interactive barrier between different network layers. Firstly, we propose a decision-level fusion method in which different weights are assigned for different data sources so that the fusion accuracy can be improved. Secondly, a hierarchical quantification approach is discussed which can avoid inferring the complex memberships among network components. Finally, a cognitive regulation mechanism is analysed in order to solve the issue of automatic control. The simulation experiments show that our model can perceive and regulate the threat situation effectively. To the best of our knowledge, this is the first discussion which utilizes cognitive awareness-control to solve the regulation problem of NSSA.
| Original language | English |
|---|---|
| Pages (from-to) | 15-30 |
| Number of pages | 16 |
| Journal | Journal of Network and Computer Applications |
| Volume | 139 |
| DOIs | |
| State | Published - 1 Aug 2019 |
Keywords
- Cognitive computing
- Cognitive control
- Multi-source fusion
- Network security situation awareness
- Reinforced learning
- Threat gene
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