g., the attack on Crypto-1, a cryptosystem for use on MIFARE chips [30].The rest of the paper is organized as follows. Section 2 introduces some general concepts about EPCG2 PRNGs and describes the structure and the characteristics of J3Gen in particular. Section 3 describes the cryptanalysis of J3Gen for two different sets of recommended parameters. Then, in Section 4, we comment on some possible modifications to improve J3Gen, and finally, Section 5 concludes the paper.2.?An EPCG2-Compliant PRNG: J3GenDefinition 1 (PRNG). 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 [31] 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 [6], these are the ��basic�� randomness criteria set by the standard:Probability of a single RN16: The probability that any RN16 drawn from the PRNG has value RN16 = j, for any j, shall be bounded by:0.8/216

25/216Probability of simultaneously identical sequences: For a tag population of up to 10,000 tags, the probability that any two or more tags simultaneously generate the same sequence of RN16s shall be less than 0.1%, regardless of when the tags are energized.Probability GSK-3 of predict
The integration of automated systems in machining processes in the absence of an operator requires not only the best selection of cutting parameters, but also the monitoring and control of the process in real time to obtain the level of quality required of the products at a high rate of productivity. In this context, in the last decades a great effort has been made towards the development of monitoring machining systems. The success of such systems is conditioned by their capability of detecting any anomaly during the machining to implement at this point the corresponding corrective actions, maintaining in this way the stability of the process, and avoid downtime of the machine.