A Study of Data Store-based Home Automation
Kaushal Kafle, Kevin Moran, Sunil Manandhar, Adwait Nadkarni, Denys, Poshyvanyk

TL;DR
This paper systematically evaluates the security of popular home automation platforms, revealing significant vulnerabilities in routine execution and access control that pose risks to user safety and privacy.
Contribution
It provides a semi-automated security analysis of Nest and Philips Hue platforms, uncovering critical flaws and highlighting the need for security by design in home automation systems.
Findings
Potential for privilege escalation via routines in Nest
Ineffectiveness of Nest's product review system against attacks
Emerging platforms may lack basic security controls
Abstract
Home automation platforms provide a new level of convenience by enabling consumers to automate various aspects of physical objects in their homes. While the convenience is beneficial, security flaws in the platforms or integrated third-party products can have serious consequences for the integrity of a user's physical environment. In this paper we perform a systematic security evaluation of two popular smart home platforms, Google's Nest platform and Philips Hue, that 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. This analysis results in ten key findings with serious security implications.…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Security and Verification in Computing · Digital and Cyber Forensics
