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Proceedings Paper

Research on immune storage anomaly detection via user access behavior
Author(s): Jianzhong Huang; Yunliang Chen; Yunfu Fang
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Paper Abstract

If an intruder uses a stolen account, the authentication sub-system will regard the intruder as a legitimate user. In order to filter out such illegal users, the storage system should be capable of the user activity diagnosis. This paper presents a novel anomaly detection scheme to monitor the user access activities using the artificial immune technique. When an access request violates the access control rule, it is regarded as Non-self, so as to provide some early warning tips to the storage security sub-system. Compared with the NIDS, the proposed scheme targets the anomaly detection at storage level and focuses on the read/write data requests. In the prophase of simulation, a set of optimal parameters of algorithm are fitted according to the mean convergence speed and detection efficiency. The simulation shows the proposed scheme can reach rather high detection rate and low false alarm rate, further validating its feasibility. Thus the storage anomaly detection would strengthen the storage early warning and improve the storage security.

Paper Details

Date Published: 19 March 2009
PDF: 5 pages
Proc. SPIE 7125, Eighth International Symposium on Optical Storage and 2008 International Workshop on Information Data Storage, 71251H (19 March 2009); doi: 10.1117/12.821631
Show Author Affiliations
Jianzhong Huang, Wuhan National Lab. for Optoelectronics, Huazhong Univ. of Science and Technology (China)
Yunliang Chen, Wuhan National Lab. for Optoelectronics, Huazhong Univ. of Science and Technology (China)
Yunfu Fang, Wuhan National Lab. for Optoelectronics, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7125:
Eighth International Symposium on Optical Storage and 2008 International Workshop on Information Data Storage
Fuxi Gan, Editor(s)

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