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A Mobile Security-Related Behavior Prevention Model Based on Speech Personality Traits

机译:基于语音个性特征的移动安全相关行为预防模型

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摘要

With the continuous development of mobile Internet, the damage due to mobile security incidents is motivating system and security application to adopt protective mechanisms. Recent research has begun to focus on the correlation between personality traits and security-related behavior such as email phishing response. In practical instances of this security domain knowledge, acquiring the user's personality accurately and conveniently in a mobile environment is desired. In this paper, considering the high efficiency of speech personality assessment, a prevention model using speech personality traits is proposed to guarantee customized security services. Our model is based on multilayer perceptron and prosodic features selection to acquire user speech personality traits. Furthermore, by combining obtained personality traits and security-related behavior domain knowledge, a prevention strategy is proposed. The proposed prevention strategy, which design is based on the correlation between user personality profile and security behavior weaknesses, is used to provide customized security prevention services. The results showed that the proposed model can achieve superior performance than other state-of-the-art speech personality assessment method and guarantee customized security-related behavior prevention support according to personality traits. The assessment time on mobile terminals is reduced to 19.2% of the traditional questionnaire method.
机译:随着移动互联网的不断发展,移动安全事件造成的破坏正在促使系统和安全应用采取保护机制。最近的研究已经开始关注人格特征与安全相关行为(例如电子邮件网络钓鱼响应)之间的相关性。在这种安全领域知识的实际实例中,期望在移动环境中准确且方便地获取用户的个性。考虑到语音人格评估的高效率,提出了一种基于语音人格特征的预防模型来保证个性化的安全服务。我们的模型基于多层感知器和韵律特征选择来获得用户语音个性特征。此外,通过结合获得的人格特质和与安全相关的行为领域知识,提出了一种预防策略。所提出的预防策略是基于用户个性配置文件与安全行为弱点之间的相关性设计的,用于提供定制的安全预防服务。结果表明,与其他最新的语音人格评估方法相比,所提模型具有更好的性能,并能根据人格特征保证定制的安全相关行为预防支持。在移动终端上的评估时间减少到传统问卷方法的19.2%。

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