Towards a Natural Perspective of Smart Homes for Practical Security and Safety Analyses
Sunil Manandhar, Kevin Moran, Kaushal Kafle, Ruhao Tang, Denys Poshyvanyk, Adwait Nadkarni
Abstract
Designing practical security systems for the smart home is challenging without the knowledge of realistic home usage. This paper describes the design and implementation of Hεlion, a framework that generates natural home automation scenarios by identifying the regularities in user-driven home automation sequences, which are in turn generated from routines created by end-users. Our key hypothesis is that smart home event sequences created by users exhibit inherent 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 Hεlion seem valid to end-users, through two studies with 16 external evaluators. We further demonstrate the usefulness of Hεlion’s scenarios by addressing the challenge of policy specification, and using Hεlion to generate 17 security/safety policies with minimal effort. We distill 16 key findings from our results that demonstrate the strengths of our approach, surprising aspects of home automation, as well as challenges and opportunities in this rapidly growing domain.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 23c89447-91bc-4f02-a4ce-7be5dcab0c0dCited by top-tier papers11
- Privacy Norms for Smart Home Personal AssistantsNoura Abdi, Xiao Zhan, Kopo M. Ramokapane, Jose M. SuchCHI 2021 · 107 citations
- Understanding IoT Security from a Market-Scale PerspectiveXin Jin, Sunil Manandhar, Kaushal Kafle, Zhiqiang Lin et al.CCS 2022 · 30 citations
- Discovering IoT Physical Channel VulnerabilitiesMuslum Ozgur Ozmen, Xuansong Li, Andrew Chu, Z. Berkay Celik et al.CCS 2022 · 25 citations
- IoTMosaic: Inferring User Activities from IoT Network Traffic in Smart HomesYinxin Wan, Kuai Xu, Feng Wang, Guoliang XueINFOCOM 2022 · 18 citations
- TAPFixer: Automatic Detection and Repair of Home Automation Vulnerabilities based on Negated-property ReasoningYinbo Yu, Yuanqi Xu, Kepu Huang, Jiajia LiuUSENIX Security 2024 · 6 citations
Builds on5
- Security Analysis of Emerging Smart Home ApplicationsEarlence Fernandes, Jaeyeon Jung, Atul PrakashS&P 2016 · 684 citations
- IoTGuard: Dynamic Enforcement of Security and Safety Policy in Commodity IoTZ. Berkay Celik, Gang Tan, Patrick D. McDanielNDSS 2019 · 254 citations
- Sensitive Information Tracking in Commodity IoTZ. Berkay Celik, Leonardo Babun, Amit Kumar Sikder, Hidayet Aksu et al.USENIX Security 2018 · 236 citations
- Fear and Logging in the Internet of ThingsQi Wang, Wajih Ul Hassan, Adam Bates, Carl A. GunterNDSS 2018 · 205 citations
- On the Safety of IoT Device Physical Interaction ControlWenbo Ding, Hongxin HuCCS 2018 · 169 citations
Related papers
- Learning from User-driven Events to Generate Automation SequencesYunpeng Song, Yiheng Bian, Xiaorui Wang, Zhongmin CaiUbiComp 2024 · 7 citations
- A User-Centric Evaluation of Smart Home Resolution Approaches for Conflicts Between RoutinesAli Zaidi, Rui Yang, Vinay Koshy, Camille Cobb et al.UbiComp 2023 · 8 citations
- SmartGen: Synthesizing Context-Aware User Behavior Data for Adaptive Smart Home IntelligenceZhiyao Xu, Dan Zhao, Qingsong Zou, Qing Li et al.KDD 2026
- Incremental Program Synthesis from Event LogsJinwoo Kim, Victor Nicolet, Joey Dodds, Loris D'AntoniOOPSLA 2026
- HAWatcher: Semantics-Aware Anomaly Detection for Appified Smart HomesChenglong Fu, Qiang Zeng, Xiaojiang DuUSENIX Security 2021 · 109 citations
