This paper focuses on developing a security mechanism geared towards appified smart-home platforms. Such platforms often expose programming interfaces for developing automation apps that mechanize different tasks among smart sensors and actuators (e.g., automatically turning on the AC when the room temperature is above 80 F). Due to the lack of effective access control mechanisms, these automation apps can not only have unrestricted access to the user's sensitive information (e.g., the user is not at home) but also violate user expectations by performing undesired actions. As users often obtain these apps from unvetted sources, a malicious app can wreak havoc on a smart-home system by either violating the user's security and privacy, or creating safety hazards (e.g., turning on the oven when no one is at home). To mitigate such threats, we propose Expat which ensures that user expectations are never violated by the installed automation apps at runtime. To achieve this goal, Expat provides a platform-agnostic, formal specification language UEI for capturing user expectations of the installed automation apps' behavior. For effective authoring of these expectations (as policies) in UEI, Expat also allows a user to check the desired properties (e.g., consistency, entailment) of them; which due to their formal semantics can be easily discharged by an SMT solver. Expat then enforces UEI policies in situ with an inline reference monitor which can be realized using the same app programming interface exposed by the underlying platform. We instantiate Expat for one of the representative platforms, OpenHAB, and demonstrate it can effectively mitigate a wide array of threats by enforcing user expectations while incurring only modest performance overhead. 
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                            Protecting Smart Homes from Unintended Application Actions
                        
                    
    
            Many smart home frameworks use applications to automate devices in a smart home. When these applications interact in the same environment, they may cause unintended actions which can lead to a safety violation (e.g., the door is unlocked when the user is not at home). While recent efforts have attempted to address this problem, they do not capture complex app behaviors such as: 1) timed behavior and user inputs (e.g., a door can remain unlocked for a long time because of a lock-door app that locks the door after 𝑥 duration, if 𝑥 is set too large.) and 2) interactions between devices and the environment they implicitly affect (e.g., water sprinklers cannot be turned on if the water supply is off). Hence, prior work leads to many false positives and false negatives. In this paper, we present PSA, a practical framework to identify safety intent violations in a smart home. PSA uses parameterized timed automata (PTA) as an expressive abstraction to model smart apps. To parse these apps into PTA, we define mappings from smart app APIs to equivalent PTA primitives. We also provide toolkits to model devices, environments, and their interactions. We evaluate PSA on 86 apps in the Samsung SmartThings IoT ecosystem. We compare PSA against two state-of-the-art baselines and find: (a) 19 new intent violations and (b) 35% fewer false positives than baselines. 
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                            - Award ID(s):
- 1801472
- PAR ID:
- 10399850
- Date Published:
- Journal Name:
- 13th ACM/IEEE International Conference on Cyber-Physical Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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