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Unfavorable Behavior Detection in Real World Systems Using the Multiagent System

机译:使用Multiagent系统的现实系统中的不良行为检测

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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,在许多现实世界的安全系统中,检测破坏性攻击和危险活动已成为至关重要的问题。安全系统应该能够区分某些行为者,哪些行为的影响可能在所考虑的区域内是不利的。所考虑的区域是现实世界的系统,例如机场,商店或市中心。现实世界安全系统的项目应假设现实世界系统中危险活动的变化和不可预测的类型。安全系统必须检测并应对从未遇到过的新型危险。在本文中,提出了一些应从允许自动入侵检测的伦理社会和免疫学机制中衍生的方法。

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