CRSep 22, 2021

SoK: Cryptographic Confidentiality of Data on Mobile Devices

arXiv:2109.11007v11 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the critical issue of data confidentiality for mobile device users, but it is incremental as it synthesizes and analyzes existing research rather than introducing new techniques.

The paper tackles the problem of protecting sensitive data on mobile devices from extraction attacks by systematizing existing cryptographic approaches and proposing a methodology for analysis. It evaluates literature and identifies gaps in securing devices against adversaries with physical and cloud access.

Mobile devices have become an indispensable component of modern life. Their high storage capacity gives these devices the capability to store vast amounts of sensitive personal data, which makes them a high-value target: these devices are routinely stolen by criminals for data theft, and are increasingly viewed by law enforcement agencies as a valuable source of forensic data. Over the past several years, providers have deployed a number of advanced cryptographic features intended to protect data on mobile devices, even in the strong setting where an attacker has physical access to a device. Many of these techniques draw from the research literature, but have been adapted to this entirely new problem setting. This involves a number of novel challenges, which are incompletely addressed in the literature. In this work, we outline those challenges, and systematize the known approaches to securing user data against extraction attacks. Our work proposes a methodology that researchers can use to analyze cryptographic data confidentiality for mobile devices. We evaluate the existing literature for securing devices against data extraction adversaries with powerful capabilities including access to devices and to the cloud services they rely on. We then analyze existing mobile device confidentiality measures to identify research areas that have not received proper attention from the community and represent opportunities for future research.

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