Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Intelligent Analysis of Database Users Based on A Dynamic Model

Authors
Jieqing Ai, Jianyong Wang, Shouming Chen, Hao Guan, Chengdong Liang, Liang Chen
Corresponding Author
Jieqing Ai
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.126How to use a DOI?
Keywords
Intelligent Analysis of Database Users Based on A Dynamic Model
Abstract
Database security issues play an important role in modern information systems. This paper aims to deal with one of the most difficult issues for database security. We propose a novel intelligent method for database user behaviour analysis. Specially, we use hidden Markov model (HMM) to model the user profile. Different from most of previous works which only focus on query syntax for anomaly analysis, our approach explores more temporal relationships between operations and can take advantage of big training data. Experimental result has shown that our model is quite effective and efficient.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Jieqing Ai
AU  - Jianyong Wang
AU  - Shouming Chen
AU  - Hao Guan
AU  - Chengdong Liang
AU  - Liang Chen
PY  - 2016/06
DA  - 2016/06
TI  - Intelligent Analysis of Database Users Based on A Dynamic Model
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SP  - 146
EP  - 150
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.126
DO  - https://doi.org/10.2991/mecs-17.2017.126
ID  - Ai2016/06
ER  -