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Unfavorable Behavior Detection in Real World Systems Using the Multiagent System

机译:使用多层系统的现实世界系统中不利行为检测

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Nowadays detecting destructive attacks and dangerous activities is crucial problem in many real world security systems. A security system should enable to distinguish some actors which effects of behavior are perhaps unfavorable for a considered area. The considered areas are real world systems e.g. airports, shops or city centers. Project of real world security system should assume the changing and unpredictable type of dangerous activities in real world systems. Security system has to detect and react to new kind of dangers that have never been encountered before. In this article there are presented methods derived from some ethically-social and immunological mechanisms that should enable automated intrusion detection.
机译:如今,检测破坏性攻击和危险活动在许多真实世界安全系统中是至关重要的问题。安全系统应使能够区分某些行为的行为可能对一个考虑的区域不利的作用。被认为是现实世界系统,例如,机场,商店或城市中心。现实世界安全系统的项目应承担现实世界系统中的变化和不可预测的危险活动。安全系统必须检测和对新的危险进行检测和反应以前从未遇到过的危险。在本文中,呈现出源自某种道德社会和免疫机制的方法,该方法应该能够实现自动入侵检测。

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