Research Article
Filtering Nonlinear Feedback Shift Registers Using Welch-Gong Transformations for Securing RFID Applications
@INPROCEEDINGS{10.1007/978-3-642-37949-9_56, author={Kalikinkar Mandal and Guang Gong}, title={Filtering Nonlinear Feedback Shift Registers Using Welch-Gong Transformations for Securing RFID Applications}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers}, proceedings_a={QSHINE}, year={2013}, month={7}, keywords={Nonlinear feedback shift registers pseudorandom sequence generators stream ciphers WG-7 stream cipher}, doi={10.1007/978-3-642-37949-9_56} }- Kalikinkar Mandal
Guang Gong
Year: 2013
Filtering Nonlinear Feedback Shift Registers Using Welch-Gong Transformations for Securing RFID Applications
QSHINE
Springer
DOI: 10.1007/978-3-642-37949-9_56
Abstract
Pseudorandom number generators play an important role to provide security and privacy on radio frequency identification (RFID) tags. In particular, the EPC Class 1 Generation 2 (EPC C1 Gen2) standard uses a pseudorandom number generator in the tag identification protocol. In this paper, we first present a pseudorandom number generator, named the filtering nonlinear feedback shift register using Welch-Gong (WG) transformations (filtering WG-NLFSR) and the filtering WG7-NLFSR for EPC C1 Gen2 RFID tags. We then investigate the periodicity of a sequence generated by the filtering WG-NLFSR by considering the model, named nonlinear feedback shift registers using Welch-Gong (WG) transformations (WG-NLFSR). The periodicity of WG-NLFSR sequences is investigated in two ways. Firstly, we perform the cycle decomposition of WG-NLFSR recurrence relations over different finite fields by computer simulations where the nonlinear recurrence relation is composed of a characteristic polynomial and a WG transformation module. Secondly, we conduct an empirical study on the period distribution of the sequences generated by the WG-NLFSR. The empirical study states that a sequence with period bounded below by the square root of the maximum period can be generated by the WG-NLFSR with high probability for any initial state.
