Evidence map›Paper›PMID 37112508›Full record

ArticleSensors (Basel, Switzerland)2023

Efficient

Dong-Hyeon Ryu, Seong-Yun Jeon, Junho Hong, Mun-Kyu Lee

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Dong-Hyeon RyuDepartment of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 37673, Republic of Korea.ORCID 0000-0002-0197-4945
Seong-Yun JeonDepartment of Computer Engineering, Inha University, Incheon 22212, Republic of Korea.ORCID 0000-0003-3563-3513
Junho HongDepartment of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA.ORCID 0000-0001-5035-8260
Mun-Kyu LeeDepartment of Computer Engineering, Inha University, Incheon 22212, Republic of Korea.ORCID 0000-0003-4423-7467
Inha University · KRPohang University of Science and Technology · KRUniversity of Michigan–Dearborn · US

Funding

Inha University Research Grant 2022Korea Institute of Energy Technology Evaluation and Planning 20214000000820
6 · The paper itself

Abstract

In Internet of Things (IoT) systems in which a large number of IoT devices are connected to each other and to third-party servers, it is crucial to verify whether each device operates appropriately. Although anomaly detection can help with this verification, individual devices cannot afford this process because of resource constraints. Therefore, it is reasonable to outsource anomaly detection to servers; however, sharing device state information with outside servers may raise privacy concerns. In this paper, we propose a method to compute the Lp distance privately for even p>2 using inner product functional encryption and we use this method to compute an advanced metric, namely

Indexed as

anomaly detectionfunctional encryptionmean p-powered error

Identifiers

PMID37112508
PMCPMC10143019
OpenAlexW4366772162

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.