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Temporal Pattern in Tweeting Behavior for Persons' Identity Verification

机译:个人身份验证鸣叫行为的时间模式

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Social interactions via Online Social Network (OSN) can provide a gamut of information about users that have been recently studied as behavioral patterns for person recognition. Similar to social interactions, the temporal information of persons in OSN is likely to exhibit behavioral characteristic and habitual pattern. This paper presents the first empirical study to answer a question whether temporal information obtained via OSN may contain sufficient behavioral biometric properties. In this paper, we present a methodology to identify a set of idiosyncratic temporal features and develop a system based on those unique features for identity verification. To the best of our knowledge, this is the first study on identity verification based on solely temporal profile obtained from an online social network. Experiments demonstrate that the proposed unique temporal profile in OSN can be utilized for users' identity verification, as it obtained low EER of 12% and high AUC of 95.2% in a closed-set test scenario. Potential applications of the proposed temporal profile include identity verification, anomaly and fraud detection, identity theft, continuous authentication, human behavior analysis, and so on.
机译:通过在线社交网络(OSN)进行的社交互动可以提供有关用户的信息,这些信息最近已被研究为人们识别的行为模式。与社交互动类似,OSN中人员的时间信息可能表现出行为特征和习惯模式。本文提出了第一个实证研究,以回答通过OSN获得的时间信息是否可能包含足够的行为生物特征的问题。在本文中,我们提出了一种方法来识别一组特有的时间特征,并基于这些独特的特征开发一个用于身份验证的系统。据我们所知,这是首次基于仅从在线社交网络获得的时间配置文件进行身份验证的研究。实验表明,在封闭测试环境中,OSN中建议的唯一时间配置文件可实现12%的低EER和95.2%的高AUC,可用于用户身份验证。提议的时间概况的潜在应用包括身份验证,异常和欺诈检测,身份盗窃,连续身份验证,人类行为分析等。

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