Monitoring User-Intent of Cloud-Based Networked Applications in Cognitive Networks.

The cognitive network system learns from the past (situations, plans, decisions, actions) and uses this knowledge to improve the decisions in the future. Scenarios in which data resources for configuring radio-system parameters are stored in the cloud for easily sharing and exchanging between nodes are foreseeable. Due to the physical inaccessibility and limited control, it is always a tough topic to formulate appropriate access control strategies for the cloud data and data access requests submitted by applications are not always correct and credible. Cloud servers cannot clearly confirm that these requests are consistent with a user's original intent. In this paper, we propose a new access control method and forensic framework for user-intent monitoring of cloud-based networked applications in cognitive networks. Our framework has two main functions. Firstly, it makes sure that every data access request submitted by applications is correct. This means that it accurately shows what it wants. Monitoring user-intent can also help the cognitive engine to make decisions in turn. Secondly, it can offer adequate details to help forensic analysts reconstruct a precise view of user interaction with applications and understand system conditions. Our framework can function correctly in untrusted environments and is transparent to applications, systems and communication environments. It incurs no discernible performance overhead.