A learning-based approach for SELinux policy optimization with type mining

Said Marouf,Doan Minh Phuong,Mohamed Shehab

CSIIRW '10: Proceedings of the Sixth Annual Workshop on Cyber Security and Information Intelligence Research（2010）

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摘要

One of the major steps towards enhancing the security of the Linux operating system was the introduction of Security Enhanced Linux (SELinux) [1], developed by the U.S. National Security Agency. SELinux is a kernel Linux Security Module (LSM) that adds Mandatory Access Control (MAC) to a regular Linux system with Discretionary Access Control (DAC) [2]. SELinux supports Type Enforcement (TE), Role Based Access Control (RBAC), and Multi-Level Security Levels (MLS).

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关键词

mandatory access control,discretionary access control,type mining,selinux policy optimization,kernel linux security module,multi-level security levels,security enhanced linux,linux operating system,u.s. national security agency,learning-based approach,access control,regular linux system,type enforcement,steganography,image compression,role based access control,jpeg,national security agency,steganalysis,operating system

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