Literature DB >> 32331407

ACD: An Adaptable Approach for RFID Cloning Attack Detection.

Weiqing Huang1,2,3, Yanfang Zhang2,3, Yue Feng2,3.   

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.

Entities:  

Keywords:  Floyd-Warshall algorithm; cloning detection; radio frequency identification (RFID)

Year:  2020        PMID: 32331407      PMCID: PMC7219334          DOI: 10.3390/s20082378

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Clone tag detection in distributed RFID systems.

Authors:  Hazalila Kamaludin; Hairulnizam Mahdin; Jemal H Abawajy
Journal:  PLoS One       Date:  2018-03-22       Impact factor: 3.240

  1 in total
  1 in total

Review 1.  Internet of Things: Security and Solutions Survey.

Authors:  Pintu Kumar Sadhu; Venkata P Yanambaka; Ahmed Abdelgawad
Journal:  Sensors (Basel)       Date:  2022-09-30       Impact factor: 3.847

  1 in total

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