EPCGen2 Pseudorandom Number Generators: Analysis of J3Gen

Peinado, Alberto; Munilla, Jorge; Fúster‐Sabater, Amparo

doi:10.3390/s140406500

Cited by 21 publications

(38 citation statements)

References 30 publications

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“…However, looking security and privacy that is beginning to be newly requested to RFID, security evaluation has not been done well. Further, there is even the security evaluation by the author, also those attacks as J3Gen [5] and Grain has been reported. There is a Warbler as one of those who have not been reported for about attack and have the security assessment to the author, but the key length is less than 80bit.…”

Section: Related Workmentioning

confidence: 99%

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New Pseudo-Random Number Generator for EPC Gen2

Nomaguchi

Miyaji

2020

IEICE Trans. Inf. & Syst.

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RFID enable applications are ubiquitous in our society, especially become more and more important as IoT management rises. Meanwhile, the concern of security and privacy of RFID is also increasing. The pseudorandom number generator is one of the core primitives to implement RFID security. Therefore, it is necessary to design and implement a secure and robust pseudo-random number generator (PRNG) for current RFID tag. In this paper, we study the security of lightweight PRNGs for EPC Gen2 RFID tag which is an EPC Global standard. For this reason, we have analyzed and improved the existing research at IEEE TrustCom 2017 and proposed a model using external random numbers. However, because the previous model uses external random numbers, the speed has a problem depending on the generation speed of external random numbers. In order to solve this problem, we developed a pseudorandom number generator that does not use external random numbers. This model consists of LFSR, NLFSR and SLFSR. Safety is achieved by using nonlinear processing such as multiplication and logical multiplication on the Galois field. The cycle achieves a cycle longer than the key length by effectively combining a plurality of LFSR and the like. We show that our proposal PRNG has good randomness and passed the NIST randomness test. We also shows that it is resistant to identification attacks and GD attacks.

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Section: Related Workmentioning

confidence: 99%

“…Next, a description will be given of WGP to be used in the WG. Input is referred to as x (x ∈ F 5 2 ). WGP is expressed by the following equation.…”

Section: Security Analysis Of Our Previous Proposal Modelmentioning

confidence: 99%

New Pseudo-Random Number Generator for EPC Gen2

Nomaguchi

Miyaji

2020

IEICE Trans. Inf. & Syst.

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“…It is also very important that the pseudo-random sequence generator algorithm is lightweight because of the limited computational, memory but also energy resources of the NB-IoT nodes [ 49 ]. Typically, this random number generator algorithm should be implementable on a basic 8-bit microcontroller and its hardware complexity in terms of its gate equivalence (GE) should prove its low complexity.…”

Section: The Proposed Intelligent Mixed Approachmentioning

confidence: 99%

A Novel Spread Spectrum and Clustering Mixed Approach with Network Coding for Enhanced Narrowband IoT (NB-IoT) Scalability

Migabo

Djouani

Kurien

2020

Sensors

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The Narrowband Internet of Things (NB-IoT) is a very promising licensed Internet of things (IoT) technology for accommodating massive device connections in 5G and beyond. To enable network scalability, this study proposes a two-layers novel mixed approach that aims not only to create an efficient spectrum sharing among the many NB-IoT devices but also provides an energy-efficient network. On one layer, the approach uses an Adaptive Frequency Hopping Spread Spectrum (AFHSS) technique that uses a lightweight and secure pseudo-random sequence to exploit the channel diversity, to mitigate inter-link and cross-technology interference. On the second layer, the approach consists of a clustering and network coding (data aggregation) approach based on an energy-signal strength mixed gradient. The second layer contributes to offload the BS, allows for energy-efficient network scalability, helps balance the energy consumption of the network, and enhances the overall network lifetime. The proposed mixed strategy algorithm is modelled and simulated using the Matrix Laboratory (MATLAB) Long Term Evolution (LTE) toolbox. The obtained results reveal that the proposed mixed approach enhances network scalability while improving energy efficiency, transmission reliability, and network lifetime when compared to the existing spread spectrum only, nodes clustering only, and mixed approach with no network coding approaches.

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“…, the LFSR clock, as well as the clock of the physical source of randomness, and the one controlling the selection of polynomials) are not synchronized. Therefore, the list of polynomials (no matter the value of ℓ ) would never be applied as suggested in [ 4 , 5 ]. This makes infeasible the deterministic attack proposed by Peinado et al , as well as all the remainder figures, algorithms and boundaries provided in their analysis of J3Gen.…”

Section: Remarks On the Peinado Et Al Analysismentioning

confidence: 99%

“…J3Gen is intended for security, improving the one-time-pad cipher unpredictability. The security of this generator was very recently claimed by Peinado et al to be weak in [ 4 , 5 ]. In their work, Peinado et al also present a deterministic attack based on the decimation of the J3Gen output sequences.…”

Section: Introductionmentioning

confidence: 99%

Remarks on Peinado et al.’s Analysis of J3Gen

García-Alfaro

Herrera-Joancomartí

Melià-Seguí

2015

Sensors

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Peinado et al. analyzed the security of the J3Gen pseudorandom number generator proposed by Melià-Seguí et al., and claimed weaknesses regarding its security properties. They also presented a deterministic attack based on the decimation of the J3Gen output sequences. We show that the assumptions made by Peinado et al. are not correct and that the proposed deterministic attack against J3Gen does not hold in practice.

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EPCGen2 Pseudorandom Number Generators: Analysis of J3Gen

Cited by 21 publications

References 30 publications

New Pseudo-Random Number Generator for EPC Gen2

New Pseudo-Random Number Generator for EPC Gen2

A Novel Spread Spectrum and Clustering Mixed Approach with Network Coding for Enhanced Narrowband IoT (NB-IoT) Scalability

Remarks on Peinado et al.’s Analysis of J3Gen

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