猜对你的密码:用公开的传感器数据解锁智能手机

David Berend, Bernhard Jungk, S. Bhasin
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引用次数: 2

摘要

现代智能手机在日常生活中扮演着同伴的角色,在远远超出沟通的任务中发挥着关键作用。配备了各种运动和健康传感器,私人信息被持续处理,而无需特别许可即可访问。在本文中,我们展示了如何使用无需许可的传感器数据来重建一个人的密码,以解锁手机或访问一个人的银行账户。利用机器学习算法的强大功能,我们提出了一种能够对所有10,000种可能的PIN组合进行分类的实用攻击。结果显示,在20次尝试中成功率高达83.7%。与目前在减少50个选定pin的空间上报告74%的成功率相比,我们在类似设置中进行一次尝试报告99.5%的成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Guessing Your PIN Right: Unlocking Smartphones with Publicly Available Sensor Data
Modern day smartphones act as daily companions playing a crucial role in tasks far beyond communication. Equipped with various motion and health sensors, private information is continuously processed, while it can be accessed without asking for special permission. In this paper, we show how the permissionless sensor data can be used to reconstruct one's secret PIN for unlocking the phone or gaining access to one's bank account. Harvesting the power of machine learning algorithms, we present a practical attack able to classify all 10,000 possible PIN combinations. Results show up to 83.7% success within 20 tries. Compared to state of the art reporting 74% success on a reduced space of 50 chosen PINs, we report 99.5% success with a single try in a similar setting.
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