Towards a Natural Perspective of Smart Homes for Practical Security and Safety Analyses

Sunil Manandhar, Kevin Moran, Kaushal Kafle, Ruhao Tang, D. Poshyvanyk, Adwait Nadkarni
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引用次数: 27

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.
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从自然的角度看智能家居的实际安全和安全分析
在不了解实际家庭使用情况的情况下,为智能家居设计实用的安全系统是具有挑战性的。本文描述了Hεlion框架的设计和实现,该框架通过识别用户驱动的家庭自动化序列中的规律来生成自然的家庭自动化场景,而用户驱动的家庭自动化序列又由最终用户创建的例程生成。我们的关键假设是,用户创建的智能家居事件序列表现出固有的语义模式,或者可以建模并用于生成有效和有用的场景的自然性。为了评估我们的方法,我们首先通过从40个用户收集的273例程构建的30,518个家庭自动化事件的语料库,实证地证明了这种自然性假设成立。然后,通过与16个外部评估者的两项研究,我们证明了Hεlion生成的场景对最终用户似乎是有效的。我们通过解决策略规范的挑战,并使用Hεlion以最小的努力生成17个安全/安全策略,进一步证明了Hεlion场景的有用性。我们从我们的结果中提炼出16个关键发现,这些发现展示了我们的方法的优势,家庭自动化的令人惊讶的方面,以及这个快速增长领域的挑战和机遇。
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