利用神经模糊技术通过分析人类的某些情绪来检测安全威胁等级

AbedAlrahman Alshawatreya, M. Malkawi, A. Albashiti
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引用次数: 0

摘要

提出了一种新的安全威胁等级检测系统,该系统基于脑电图、心率等人体生理变量来检测愤怒、恐惧、焦虑、害怕迫在眉睫的威胁等一系列负面情绪,这些情绪被认为是安全相关情绪。基于检测到的情绪,提出的模型将能够确定安全威胁级别,例如低、中、高、重大和关键。提出了几种模型;每个对应一个特定的安全警报需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The detection of security threat level by analyzing certain human emotions using neuro-fuzzy techniques
A novel security threat level detection system is proposed based on a number of human physiological variables such as electroencephalography, heart rate and others which are utilized to detect a set of negative emotions such as anger, fear, anxiety, and fear imminent threat, which are considered as security related emotions. Based on the detected emotions the proposed model will be able to determine the security threat level, e.g. low, moderate, high, substantial, and critical. Several models are presented; each corresponds to a particular security alert demand.
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