TY - JOUR
T1 - Monitoring User-Intent of Cloud-Based Networked Applications in Cognitive Networks
AU - Liu, Xuanyu
AU - Fu, Xiao
AU - Luo, Bin
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
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U2 - 10.1109/GLOCOM.2018.8647499
DO - 10.1109/GLOCOM.2018.8647499
M3 - Conference article
AN - SCOPUS:85063425456
SN - 2334-0983
JO - Proceedings - IEEE Global Communications Conference, GLOBECOM
JF - Proceedings - IEEE Global Communications Conference, GLOBECOM
M1 - 8647499
T2 - 2018 IEEE Global Communications Conference, GLOBECOM 2018
Y2 - 9 December 2018 through 13 December 2018
ER -