Demo Data from VLDB 2026 / reviewers in the wild / expert
Ruhao Tang
dblp:244/2204
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Cyber-physical and IoT security · 77% Systems and software security · 23% | |
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments
smart home |
0.4 | 1 | 2020 | Towards a Natural Perspective of Smart Homes for Practical Security and Safety Analyses · SP 2020 |
Systems and software security
security policy specification |
0.1 | 1 | 2020 | Towards a Natural Perspective of Smart Homes for Practical Security and Safety Analyses · SP 2020 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9naturalness modeling · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Towards a Natural Perspective of Smart Homes for Practical Security and Safety AnalysesabstractDesigning 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. Sunil Manandhar, Kevin Moran, Kaushal Kafle, Ruhao Tang, Denys Poshyvanyk, Adwait Nadkarni |
SP | 4 |