arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2210.04777cs.CRcs.LG
收藏

mPSAuth:面向移动 Web 应用的隐私保护且可扩展的身份认证

mPSAuth: Privacy-Preserving and Scalable Authentication for Mobile Web Applications

Institute of Applied Research (IAF), Karlsruhe University of Applied Sciences(卡尔斯鲁厄应用技术大学应用研究所)

David Monschein, Oliver P. Waldhorst

AI总结:

针对移动 Web 行为认证中的隐私与可扩展性问题,本文提出 mPSAuth,在同态加密数据上运行认证协议和与用户数解耦的机器学习模型,并在真实移动应用数据上验证其高准确率与低开销。

摘要:

如今,由于大多数 Web 应用请求都源自移动设备,因此从安全角度考虑,对移动用户进行身份认证至关重要。为此,近期的方法依赖机器学习技术来分析用户行为的各个方面,并将其作为身份认证决策的基础。这些方法面临两个挑战:第一,检查行为数据会引发严重的隐私担忧;第二,相关方法必须能够扩展以支持大量用户。现有方法未能充分解决这些挑战。我们提出 mPSAuth,这是一种持续跟踪反映用户行为的各类数据源(例如触摸屏交互、传感器数据)并基于机器学习技术估计当前用户为合法用户的可能性的方法。借助 mPSAuth,身份认证协议和机器学习模型都在同态加密数据上运行,以确保用户隐私。此外,mPSAuth 使用的机器学习模型数量与用户数量无关,从而提供足够的可扩展性。在基于某移动应用真实数据开展的广泛评估中,我们说明 mPSAuth 能够以较低的加密和通信开销提供较高准确率,而推理所需的代价仅增加到可容忍的程度。

英文摘要:

As nowadays most web application requests originate from mobile devices, authentication of mobile users is essential in terms of security considerations. To this end, recent approaches rely on machine learning techniques to analyze various aspects of user behavior as a basis for authentication decisions. These approaches face two challenges: first, examining behavioral data raises significant privacy concerns, and second, approaches must scale to support a large number of users. Existing approaches do not address these challenges sufficiently. We propose mPSAuth, an approach for continuously tracking various data sources reflecting user behavior (e.g., touchscreen interactions, sensor data) and estimating the likelihood of the current user being legitimate based on machine learning techniques. With mPSAuth, both the authentication protocol and the machine learning models operate on homomorphically encrypted data to ensure the users' privacy. Furthermore, the number of machine learning models used by mPSAuth is independent of the number of users, thus providing adequate scalability. In an extensive evaluation based on real-world data from a mobile application, we illustrate that mPSAuth can provide high accuracy with low encryption and communication overhead, while the effort for the inference is increased to a tolerable extent.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑