Sunil Manandhar

Sunil Manandhar, Kevin Moran, Kaushal Kafle et al.

Security researchers have recently discovered significant security and safety issues related to home automation and developed approaches to address them. Such approaches often face design and evaluation challenges which arise from their restricted perspective of home automation that is bounded by the IoT apps they analyze. The challenges of past work can be overcome by relying on a deeper understanding of realistic home automation usage. More specifically, the availability of natural home automation scenarios, i.e., sequences of home automation events that may realistically occur in an end-user's home, could help security researchers design better security/safety systems. This paper presents Helion, a framework for building a natural perspective of home automation. Helion identifies the regularities in user-driven home automation, i.e., from user-driven routines that are increasingly being created by users through intuitive platform UIs. Our intuition for designing Helion is that smart home event sequences created by users exhibit an inherent set of semantic patterns, or naturalness that can be modeled and used to generate valid and useful scenarios. To evaluate our approach, we first empirically demonstrate that this naturalness hypothesis holds, with a corpus of 30,518 home automation events, constructed from 273 routines collected from 40 users. We then demonstrate that the scenarios generated by Helion are reasonable and valid from an end-user perspective, through an evaluation with 16 external evaluators. We further show the usefulness of Helion's scenarios by generating 17 home security/safety policies with significantly less effort than existing approaches. We conclude by discussing key takeaways and future research challenges enabled by Helion's natural perspective of home automation.

Sigmund Albert Gorski, Benjamin Andow, Adwait Nadkarni et al.

Billions of users rely on the security of the Android platform to protect phones, tablets, and many different types of consumer electronics. While Android's permission model is well studied, the enforcement of the protection policy has received relatively little attention. Much of this enforcement is spread across system services, taking the form of hard-coded checks within their implementations. In this paper, we propose Authorization Check Miner (ACMiner), a framework for evaluating the correctness of Android's access control enforcement through consistency analysis of authorization checks. ACMiner combines program and text analysis techniques to generate a rich set of authorization checks, mines the corresponding protection policy for each service entry point, and uses association rule mining at a service granularity to identify inconsistencies that may correspond to vulnerabilities. We used ACMiner to study the AOSP version of Android 7.1.1 to identify 28 vulnerabilities relating to missing authorization checks. In doing so, we demonstrate ACMiner's ability to help domain experts process thousands of authorization checks scattered across millions of lines of code.

Kaushal Kafle, Kevin Moran, Sunil Manandhar et al.

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. For instance, we demonstrate the potential for the misuse of smart home routines in the Nest platform to perform a lateral privilege escalation, illustrate how Nest's product review system is ineffective at preventing multiple stages of this attack that it examines, and demonstrate how emerging platforms may fail to provide even bare-minimum security by allowing apps to arbitrarily add/remove other apps from the user's smart home. Our findings draw attention to the unique security challenges of platforms that execute routines via centralized data stores and highlight the importance of enforcing security by design in emerging home automation platforms.