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Nowhere to Hide: Efficiently Identifying Probabilistic Cloning Attacks in Large-Scale RFID Systems.
- Source :
- IEEE Transactions on Information Forensics & Security; 2021, Vol. 16, p714-727, 14p
- Publication Year :
- 2021
-
Abstract
- Radio-Frequency Identification (RFID) is an emerging technology which has been widely applied in various scenarios, such as tracking, object monitoring, and social networks, etc. Cloning attacks can severely disturb the RFID systems, such as missed detection for the missing tags. Although there are some techniques with physical architecture design or complicated encryption and cryptography proposed to prevent the tags from being cloned, it is difficult to definitely avoid the cloning attack. Therefore, cloning attack detection and identification are critical for the RFID systems. Prior works rely on that each clone tag will reply to the reader when its corresponding genuine tag is queried. In this article, we consider a more general attack model, in which each clone tag replies to the reader’s query with a predefined probability, i.e., attack probability. We concentrate on identifying the tags being attacked with the probability no less than a threshold $P_{t}$ with the required identification reliability $\alpha $. We first propose a basic protocol to Identify the Probabilistic Cloning Attacks with required identification reliability for the large-scale RFID systems called IPCA. Then we propose two enhanced protocols called MS-IPCA and S-IPCA respectively to improve the identification efficiency. We theoretically analyze the parameters of the proposed IPCA, MS-IPCA and S-IPCA protocols to maximize the identification efficiency. Finally we conduct extensive simulations to validate the effectiveness of the proposed protocols. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15566013
- Volume :
- 16
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Information Forensics & Security
- Publication Type :
- Academic Journal
- Accession number :
- 170411629
- Full Text :
- https://doi.org/10.1109/TIFS.2020.3023785