Statistical and fuzzy approach for database security

被引：0
|
作者：
Lu, Gang [1 ]
Yi, Junkai [1 ]
Lue, Kevin [2 ]
机构：
[1] Beijing Inst Chem Technol, Sch Informat Sci & Technol, Beijing 100029, Peoples R China
[2] Brunel Univ, Uxbridge UB8 3PH, Middx, England
来源：
FOURTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/FSKD.2007.531
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new type of database anomaly is described by addressing the concept of Cumulated Anomaly in this paper. Dubiety-Determining Model (DDM), which is a detection model basing on statistical and fuzzy set theories for Cumulated Anomaly, is proposed. DDM can measure the dubiety degree of each database transaction quantitatively. Software system architecture to support the DDM for monitoring database transactions is designed. We also implemented the system and tested it. Our experimental results show that the DDM method is feasible and effective.
引用
收藏
页码：670 / +
页数：2
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