Title: A knowledgebase insider threat mitigation model in the cloud: a proactive approach

Authors: Qutaibah Althebyan; Yaser Jararweh; Qussai Yaseen; Rami Mohawesh

Addresses: Software Engineering Department, Jordan University of Science and Technology, Irbid, 22110, Jordan ' Computer Science Department, Jordan University of Science and Technology, Irbid, 22110, Jordan ' Computer Science Department, Jordan University of Science and Technology, Irbid, 22110, Jordan ' Computer Science Department, Jordan University of Science and Technology, Irbid, 22110, Jordan

Abstract: Security of cloud computing is a major concern for both organisations and individuals. The cloud users want to make sure that their private data will be safe from disclosure of both outsiders of the cloud as well as from (probably malicious) insiders (cloud agents) of the cloud. Hence, insiders' threats of the cloud computing is a major issue that needs to be tackled and resolved. In this paper, we propose a proactive insider threat model using a knowledgebase approach. Proactive in a sense that our model tries to detect (in advance) any deliberate deviation of the legal accesses an insider might try to perform so that the individuals' private data will be protected and secured. At the same time the cloud resources will be insured to be secured as well as consistent at all times. Knowledgebase models were used earlier in preventing insider threats in both the system level and the database level. This knowledgebase work will be extended to cloud computing systems.

Keywords: insider; proactive; cloud data centre; knowledgebase; prediction; mitigation.

DOI: 10.1504/IJAIP.2020.106039

International Journal of Advanced Intelligence Paradigms, 2020 Vol.15 No.4, pp.417 - 436

Received: 27 Feb 2017
Accepted: 09 Aug 2017
Published online: 26 Mar 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article