Evidence map›Paper›PMID 32331407›Full record

ArticleSensors (Basel, Switzerland)2020

ACD: An Adaptable Approach for RFID Cloning Attack Detection.

Weiqing Huang, Yanfang Zhang, Yue Feng

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.9field-weighted citation impact, top 11% 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

1 citing paper in PubMed, 13 citations in OpenAlex.

  1. Internet of Things: Security and Solutions Survey.Sensors (Basel, Switzerland) · 2022
    Review
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

3 authors at 1 institution in 1 country.

Weiqing HuangSchool of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China.
Yanfang ZhangInstitute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China.ORCID 0000-0003-0119-7741
Yue FengInstitute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China.
Chinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 61501458
6 · The paper itself

Abstract

With the rapid development of the internet of things, radio frequency identification (RFID) technology plays an important role in various fields. However, RFID systems are vulnerable to cloning attacks. This is the fabrication of one or more replicas of a genuine tag, which behave exactly as a genuine tag and fool the reader to gain legal authorization, leading to potential financial loss or reputation damage. Many advanced solutions have been proposed to combat cloning attacks, but they require extra hardware resources, or they cannot detect a clone tag in time. In this article, we make a fresh attempt to counterattack tag cloning based on spatiotemporal collisions. We propose adaptable clone detection (ACD), which can intuitively and accurately display the positions of abnormal tags in real time. It uses commercial off-the-shelf (COTS) RFID devices without extra hardware resources. We evaluate its performance in practice, and the results confirm its success at detecting cloning attacks. The average accuracy can reach 98.7%, and the recall rate can reach 96%. Extensive experiments show that it can adapt to a variety of RFID application scenarios.

Indexed as

cloning detectionFloyd-Warshall algorithmradio frequency identification (RFID)

Identifiers

PMID32331407
PMCPMC7219334
OpenAlexW3020625098

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.