Automatic Rule Extraction from Access Rules Using Genetic Programming

被引：0

作者：

de las Cuevas, Paloma ^{[1
,2
]}

Garcia-Sanchez, Pablo ^{[3
]}

Dagdia, Zaineb Chelly ^{[4
,5
]}

Garcia-Arenas, Maria-Isabel ^{[1
,2
]}

Guervos, Julian Merelo ^{[1
,2
]}

机构：

[1] Univ Granada, Dept Comp Architecture & Comp Technol, ETSIIT, Granada, Spain

[2] Univ Granada, CITIC, Granada, Spain

[3] Univ Cadiz, ESI, Dept Comp Engn, Cadiz, Spain

[4] Univ Lorraine, CNRS, INRIA, LORIA, F-54000 Nancy, France

[5] Inst Super Gest Tunis, LARODEC, Bouchoucha, Tunisia

来源：

APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2020 | 2020年 / 12104卷

关键词：

Security; Corporate Security Policy; Genetic Programming; Rule extraction; Bring your own device;

D O I：

10.1007/978-3-030-43722-0_4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The security policy rules in companies are generally proposed by the Chief Security Officer (CSO), who must, for instance, select by hand which access events are allowed and which ones should be forbidden. In this work we propose a way to automatically obtain rules that generalise these single-event based rules using Genetic Programming (GP), which, besides, should be able to present them in an understandable way. Our GP-based system obtains good dataset coverage and small ratios of false positives and negatives in the simulation results over real data, after testing different fitness functions and configurations in the way of coding the individuals.

引用

页码：54 / 69

页数：16

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