This paper analyzes the cryptographic security of J3Gen, a promising pseudo random number generator for low-cost passive Radio Frequency Identification (RFID) tags. Although J3Gen has been shown to fulfill the randomness criteria set by the EPCglobal Gen2 standard and is intended for security applications, we describe here two cryptanalytic attacks that question its security claims: (i) a probabilistic attack based on solving linear equation systems; and (ii) a deterministic attack based on the decimation of the output sequence. Numerical results, supported by simulations, show that for the specific recommended values of the configurable parameters, a low number of intercepted output bits are enough to break J3Gen. We then make some recommendations that address these issues. 2. An EPCG2-Compliant PRNG: J3Gen Definition 1 (PRNG).
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A PRNG is a pseudo-random bit generator (PRG) whose output is partitioned into blocks of a given length, n. Each block defines an n-bit number, said to be drawn from the PRNG. Definition 2 (PRG). A PRG is a deterministic algorithm that, on inputting a binary string of length K, called the seed, generates a binary sequence, s, of length S >>K which “appears” to be random. While it is very difficult to give a mathematical proof that a PRNG is indeed secure, we gain confidence by subjecting it to a variety of statistical tests designed to detect the specific characteristics expected of random sequences (we refer the reader to [] for a comprehensive collection of randomness tests).
Although the new version of EPCG2 explains that the different implemented cryptographic suites may define more stringent requirements for the PRNG [], these are the “basic” randomness criteria set by the standard: •. Probability of predicting an RN16: An RN16 drawn from a tag's PRNG shall not be predictable with a probability better than 0.025%, when the outcomes of prior draws from the PRNG under identical conditions are known. According to the authors, J3Gen amply fulfills these requirements, providing a high level of security (an equivalent key size of 372 bits). We find, however, some flaws in the design of this PRNG that question the validity of this proposal. Before analyzing these issues, we describe the structure and the characteristics of J3Gen. Description of J3Gen J3Gen is based on a dynamic linear feedback shift register (DLFSR) of n cells.
A DLFSR can be defined, in turn, as an LFSR [] where the feedback polynomial, p i( x), is not static, but changes dynamically []. J3Gen combines this DLFSR topology with a physical source of true randomness (thermal), which generates a “true random bit”, denoted by trn. This bit controls the change of polynomials, preventing the linear behavior of the DLFSR. This trn is replaced by a PRNG in []. Sizzla Praise Ye Jah Rar Download.
Depicts the block diagram of J3Gen. A set of m primitive feedback polynomials are implemented as a wheel, and the polynomial selector rotates one position if trn = 0 and two positions (one position at one shift cycle and another at the next shift cycle) if trn = 1. These rotations are performed every l cycles, with 1 ≤ l. Block diagram of J3Gen. PRNG, pseudo-random number generator; LFSR, linear feedback shift register.
For a better understanding of the functioning of J3Gen, we review here the sample of the execution provided in []. The parameter configuration chosen for this example is: n = 16, m = 8 and l = 15. The value n = 16 for the LFSR size is selected because of compatibility reasons with EPCG2 (although larger values of n are also considered in []).
The selected feedback polynomials ( m = 8) should remain secret, since they can be considered as the secret key of the system. In [], the LFSR states for 32 shift cycles are detailed, providing 32 output bits. Two true random values are used, which are set to trn 1 = 0 and trn 2 = 1. The system starts with p 1( x) and outputs 15 (= l) bits until the TRNGmodule transfers trn 1 = 0 to the decoding logic module. Then, p 2( x) is selected, and another 15 bits are generated, until the next (after l shift cycles) trn is obtained.
Brand Examples Of Intensive Distribution more. As trn 2 = 1, the decoding logic rotates the polynomial selector one position at Shift 31 and another position at Shift 32. Eventually, two 16-bit pseudorandom numbers are generated; for the first one, p 1( x) is used 15 cycles and p 2( x) one cycle, while for the second one, p 2( x) is used 14 cycles and then p 3( x) and p 4( x) are used for one cycle each ( p 4 will also be used 14 cycles for the next 16-bit pseudorandom number).