On the probability of overlap of random subsequences of pseudorandom number generators

Vigna, Sebastiano

doi:10.1016/j.ipl.2020.105939

Cited by 4 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A pseudo random generator for cryptographic applications has been shown in [28]. Several studies were carried out in this domain for validation of random numbers and generation of random numbers as shown in [29][30][31][32][33]. Such studies show that random numbers are in real need for various applications and their design factors are also very important.…”

Section: Related Workmentioning

confidence: 99%

“…We chose some recent works from the literature for comparing the results and to validate the randomness efficiency of SRFG. The algorithms described in [26,27,29,[31][32][33] exhibit true randomness and therefore have been considered for the comparison with SRFG. Another recent algorithm depicted in [18] is also considered for comparison due to its related features.…”

Section: Comparative Analysismentioning

confidence: 99%

See 1 more Smart Citation

A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

et al. 2021

View full text Add to dashboard Cite

Cryptographic algorithms and functions should possess some of the important functional requirements such as: non-linearity, resiliency, propagation and immunity. Several previous studies were executed to analyze these characteristics of the cryptographic functions specifically for Boolean and symmetric functions. Randomness is a requirement in present cryptographic algorithms and therefore, Symmetric Random Function Generator (SRFG) has been developed. In this paper, we have analysed SRFG based on propagation feature and immunity. Moreover, NIST recommended statistical suite has been tested on SRFG outputs. The test values show that SRFG possess some of the useful randomness properties for cryptographic applications such as individual frequency in a sequence and block-based frequency, long run of sequences, oscillations from 0 to 1 or vice-versa, patterns of bits, gap bits between two patterns, and overlapping block bits. We also analyze the comparison of SRFG and some existing random number generators. We observe that SRFG is efficient for cryptographic operations in terms of propagation and immunity features.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Assignment (17) executed by condition (16) for subset (14) implies that, in a case when there are two or more maximal decisive ratios in (14), the earliest job is preferred to be scheduled [7]. Thus, job n is completed after moment θ( ; )…”

Section: The Heuristic Based On Remaining Available and Processing Periodsmentioning

confidence: 99%

“…Fig. 2 contains the results of the same computational experiment repeated by another randomizer [13,14]. Now, average relative difference .…”

Section: Computational Studymentioning

confidence: 99%

Tight-Tardy Progressive Idling-Free 1-Machine Preemptive Scheduling With Job Priority Weights by Heuristic’s Efficient Job Order Input

Romanuke

2021

KPI SN

View full text Add to dashboard Cite

Background. In setting a problem of minimizing total weighted tardiness by the heuristic based on remaining available and processing periods, there are two opposite ways to input the data: the job release dates are given in either ascending or descending order. It was recently ascertained that scheduling a few equal-length jobs is expectedly faster by ascending order, whereas scheduling 30 to 70 equal-length jobs is 1.5 % to 2.5 % faster by descending order. For the number of equal-length jobs between roughly 90 and 250, the ascending job order again results in shorter computation times. In the case when the jobs have different lengths, the significance of the job order input is much lower. On average, the descending job order input gives a tiny advantage in computation time. This advantage decreases as the number of jobs increases. Objective. The goal is to ascertain whether the job order input is significant in scheduling by using the heuristic for the case when the jobs have different lengths with job priority weights. Job order efficiency will be studied on tight-tardy progressive idling-free 1-machine preemptive scheduling. Methods. To achieve the said goal, a computational study is carried out with a purpose to estimate the averaged computation time for both ascending and descending orders of job release dates. First, the computation time for the ascending job order input is estimated for a series of job scheduling problems. Then, in each instance of this series, job lengths, priority weights, release dates, and due dates are reversed making thus the respective instance for the descending job order input, for which computation time is estimated as well. Results. The significance of the job order input is much lower than that for the case of jobs without priorities. With assigning the job priority weights, the job order input becomes further “dithered”, adding randomly scattered priority weights to randomly scattered job lengths and partially randomized due dates. On average, the descending job order input is believed to give a tiny advantage in computation time in scheduling up to 100 jobs. However, this advantage, if any (being tinier than that in the case of random job lengths without priorities), quickly vanishes as the number of jobs increases. Conclusions. It is better to compose job scheduling problems which would be closer to the case with equal-length jobs without priorities, where the saved computational time can be counted in hours. Even if the job lengths and priority weights are scattered, it is recommended to artificially “flatten” them. When artificial manipulations over job processing periods and job priority weights are impossible, it is recommended to use the descending job order input in scheduling up to 100 jobs, and either job order input in scheduling more than 100 jobs, although substantial benefits are not expected in this case.

show abstract

A Fast Hardware Pseudorandom Number Generator Based on xoroshiro128

Hanlon

Felix

2023

IEEE Trans. Comput.

View full text Add to dashboard Cite

On the probability of overlap of random subsequences of pseudorandom number generators

Cited by 4 publications

References 4 publications

A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions

Tight-Tardy Progressive Idling-Free 1-Machine Preemptive Scheduling With Job Priority Weights by Heuristic’s Efficient Job Order Input

A Fast Hardware Pseudorandom Number Generator Based on xoroshiro128

Contact Info

Product

Resources

About