ArticleSensors (Basel, Switzerland)2020
ACD: An Adaptable Approach for RFID Cloning Attack Detection.
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.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 13 citations in OpenAlex.
- Internet of Things: Security and Solutions Survey.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
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.