Agent-based risk learning for computing systems

被引：0
|
作者：
Wang, XF [1 ]
Kiliccote, H [1 ]
Khosla, PK [1 ]
Zhang, CQ [1 ]
机构：
[1] Carnegie Mellon Univ, Inst Complex Engineered Syst, Pittsburgh, PA 15213 USA
来源：
FOURTH INTERNATIONAL CONFERENCE ON MULTIAGENT SYSTEMS, PROCEEDINGS | 2000年
关键词：
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：
Excessive or inadequate security controls can impair the utility of an open computing system. The agent based open computing environment we propose in this paper balances the amount of security control to maximize the utility of the system. In the system, intelligent agents learn the risk of the users and then dynamically adjust the security policy to achieve better system utility.
引用
收藏
页码：459 / 460
页数：2
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