通过输入热图保护智能手机

Frankie Inguanez, S. Ahmadi
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引用次数: 8

摘要

智能手机是唯一使用最多的设备,它能够持续跟踪和监控我们的活动,从中可以检测到我们的打字等特征。各种情况,如手机丢失,传递给家人或朋友,要求我们考虑连续的被动认证模式。本文探讨了输入热图如何改善触摸设备的用户认证。通过重新审视传统的打字有向图间隔(通常与打字生物识别用户认证相关),本研究调查了智能手机上用户识别的各种功能的强度。考虑到与机械键盘或压敏平板电脑相比,在便携式小型设备上打字的方法不同,本研究将触摸屏数据呈现出一组新的特征,可以作为连续认证的被动模式。考虑到用户对设备的持续使用,多层感知器神经网络被认为是一种可行的方法,这在智能手机上也没有得到充分的研究。这项研究的结果强调了打字签名中各种与触摸相关的特征的强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Securing smartphones via typing heat maps
Smartphones are the singular most utilised device able to track and monitor our activity continuously from which signatures such as our typing can be detecting. Various situations such as loss of phone, passing on to family members or friends require us to consider continuous modes of passive authentication. This paper explores how typing heat maps can improve user authentication for touch enabled devices. By revisiting the traditional typing digraph intervals, normally associated with typing biometric user authentication, this research investigates the strength of various features for user identification on smartphones. Considering the different methods of typing on a portable small device as opposed to the mechanical keyboard or pressure sensitive tablets, this research takes the touch screen data to present a new set of features which can be used as a passive mode of continuous authentication. Given the continuous use of the device by the owner, a multilayer perceptron neural network is believed to be a plausible and viable approach for this task, which is also understudied for smartphones. The findings in this research highlight the strength of various touch related features in typing signatures.
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