Misuse detection - A neural network vs. a genetic algorithm approach

被引：0

作者：

Diaz-Gomez, Pedro A. ^{[1
]}

Hougen, Dean F. ^{[1
]}

机构：

[1] Univ Oklahoma, Sch Comp Sci, REAL Lab, Norman, OK 73019 USA

来源：

ICEIS 2007: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS | 2007年

关键词：

misuse detection; genetic algorithms; neural networks; false negative; false positive;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Misuse detection can be addressed as an optimization problem, where the problem is to find an array of possible intrusions x that maximizes a function f(.) subject to a constraint r imposed by a user's actions performed on a computer. This position paper presents and compares two ways of finding x, in audit data, by using neural networks and genetic algorithms.

引用

页码：459 / 462

页数：4

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