Security in Centralized Data Store-based Home Automation Platforms

Author:

Kafle Kaushal1,Moran Kevin2,Manandhar Sunil1,Nadkarni Adwait1,Poshyvanyk Denys1

Affiliation:

1. William & Mary, United States of America, Williamsburg, VA

2. George Mason University, United States of America, Fairfax, VA

Abstract

Home automation platforms enable consumers to conveniently automate various physical aspects of their homes. However, the security flaws in the platforms or integrated third-party products can have serious security and safety implications for the user’s physical environment. This article describes our systematic security evaluation of two popular smart home platforms, Google’s Nest platform and Philips Hue, which implement home automation “routines” (i.e., trigger-action programs involving apps and devices) via manipulation of state variables in a centralized data store . Our semi-automated analysis examines, among other things, platform access control enforcement, the rigor of non-system enforcement procedures, and the potential for misuse of routines, and it leads to 11 key findings with serious security implications. We combine several of the vulnerabilities we find to demonstrate the first end-to-end instance of lateral privilege escalation in the smart home, wherein we remotely disable the Nest Security Camera via a compromised light switch app. Finally, we discuss potential defenses, and the impact of the continuous evolution of smart home platforms on the practicality of security analysis. Our findings draw attention to the unique security challenges of smart home platforms and highlight the importance of enforcing security by design.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference66 articles.

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