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Daye Song

dblp:374/8533 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0004-2981-9113ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

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.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Network and information security
1 paper
Authentication and access control · 100%
Human-computer interaction and pervasive computing
1 paper
User interface design and tools · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
iot platform
0.812024
FLUID-IoT : Flexible and Fine-Grained Access Control in Shared IoT Environments via Multi-user UI Distribution · CHI 2024
Authentication and access control › access control
fine-grained access control
0.812024
FLUID-IoT : Flexible and Fine-Grained Access Control in Shared IoT Environments via Multi-user UI Distribution · CHI 2024

Methods — techniques the papers use, named apart from their topics

user study · 2.3performance evaluation · 2.3
YearPublicationVenuePosition
2024 FLUID-IoT : Flexible and Fine-Grained Access Control in Shared IoT Environments via Multi-user UI Distribution
abstract
The rapid growth of the Internet of Things (IoT) in shared spaces has led to an increasing demand for sharing IoT devices among multiple users. Yet, existing IoT platforms often fall short by offering an all-or-nothing approach to access control, not only posing security risks but also inhibiting the growth of the shared IoT ecosystem. This paper introduces FLUID-IoT, a framework that enables flexible and granular multi-user access control, even down to the User Interface (UI) component level. Leveraging a multi-user UI distribution technique, FLUID-IoT transforms existing IoT apps into centralized hubs that selectively distribute UI components to users based on their permission levels. Our performance evaluation, encompassing coverage, latency, and memory consumption, affirm that FLUID-IoT can be seamlessly integrated with existing IoT platforms and offers adequate performance for daily IoT scenarios. An in-lab user study further supports that the framework is intuitive and user-friendly, requiring minimal training for efficient utilization.
Sunjae Lee, Minwoo Jeong, Daye Song, Junyoung Choi 0002, Seoyun Son, Jean Y. Song, Insik Shin
CHI3