On the correlation and sensitivity of so far statistical randomness tests based on runs

Abstract—Random numbers play a very important role in cryptography. More precisely, almost cryptographic primitives are ensured their security based on random values such as random key, nonces, salts... Therefore, the assessment of randomness according to statistical tests is really essential for measuring the security of cryptographic algorithms. In this paper, we focus on so far randomness tests based on runs in the literature. First, we have proved in detail that the expected number of gaps (or blocks) of length in a random sequence of length is . Secondly, we have evaluated correlation of some tests based on runs so far using Pearson coefficient method [5, 6] and Fail-Fail ratio one [7, 8]. Surprisingly, the Pearson coefficient method do not show any strong linear correlation of these runs-based tests but the Fail-Fail ratio do. Then, we have considered the sensitivity of these runs tests with some basic transformations. Finally, we have proposed some new runs tests based on the sensitivity results and applied evaluations to some random sources. Tóm tắt—Số ngẫu nhiên đóng một vai trò quan trọng trong mật mã. Cụ thể, độ an toàn của hầu hết các nguyên thủy mật mã đều được đảm bảo dựa trên các giá trị ngẫu nhiên như khóa, nonce, salt… Do đó, việc đánh giá tính ngẫu nhiên dựa trên các kiểm tra thống kê là thực sự cần thiết để đo độ an toàn cho các thuật toán mật mã. Trong bài báo này, chúng tôi tập trung vào các kiểm tra ngẫu nhiên dựa vào run trong các tài liệu. Đầu tiên, chúng tôi chứng minh chi tiết rằng kỳ vọng số các gap (khối) độ dài trong một chuỗi ngẫu nhiên độ dài là . Sau đó, chúng tôi đánh giá mối tương quan của một số kiểm tra dựa vào run bằng phương pháp hệ số Pearson [5, 6] và tỷ số Fail-Fail [7, 8]. Đáng ngạc nhiên là phương pháp hệ số Pearson không cho thấy bất kỳ mối tương quan tuyến tính mạnh nào của các kiểm tra dựa vào run, trong khi đó tỷ số Fail-Fail lại chỉ ra. Tiếp theo, chúng tôi xem xét độ nhạy của các kiểm tra run này với một số phép biến đổi cơ bản. Cuối cùng, chúng tôi đề xuất một số kiểm tra run mới dựa trên các kết quả độ nhạy và đánh giá áp dụng chúng cho một số nguồn ngẫu nhiên.

Color Image Encryption Scheme Based On Alternate Quantum Walk and Controlled Rubik’s Cube

Aiming at solving the trouble that digital image information is easily intercepted and tampered during transmission, we proposed a color image encryption scheme based on alternate quantum random walk and controlled Rubik’s Cube transformation. At the first, the color image is separated into three channels: channel R, channel G and channel B. Besides, a random sequence is generated by alternate quantum walk. Then the six faces of the Rubik’s Cube are decomposed and arranged in a specific order on a two-dimensional plane, and each pixel of the image is randomly mapped to the Rubik’s Cube. The whirling of the Rubik’s Cube is controlled by a random sequence to realize image scrambling and encryption. The scrambled image acquired by Rubik’s Cube whirling and the random sequence received by alternate quantum walk are bitwise-XORed to obtain a single-channel encrypted image. Finally the three-channel image is merged to acquire the final encrypted image. The decryption procedure is the reverse procedure of the encryption procedure. The key space of this scheme is theoretically infinite. After simulation experiments, the information entropy after encryption reaches 7.999, the NPCR is 99.5978%, and the UACI is 33.4317%. The encryption scheme with high robustness and security has a excellent encryption effect which is effective to resist statistical attacks, force attacks, and other differential attacks.

Effects of the Expression of Random Sequence Clones on Growth and Transcriptome Regulation in Escherichia coli

Comparative genomic analyses have provided evidence that new genetic functions can emerge out of random nucleotide sequences. Here, we apply a direct experimental approach to study the effects of plasmids harboring random sequence inserts under the control of an inducible promoter. Based on data from previously described experiments dealing with the growth of clones within whole libraries, we extracted specific clones that had shown either negative, neutral or positive effects on relative cell growth. We analyzed these individually with respect to growth characteristics and the impact on the transcriptome. We find that candidate clones for negative peptides lead to growth arrest by eliciting a general stress response. Overexpression of positive clones, on the other hand, does not change the exponential growth rates of hosts, and they show a growth advantage over a neutral clone when tested in direct competition experiments. Transcriptomic changes in positive clones are relatively moderate and specific to each clone. We conclude from our experiments that random sequence peptides are indeed a suitable source for the de novo evolution of genetic functions.

Effects of Virtual Reality-Based Relaxation Techniques on Psychological, Physiological, and Biochemical Stress Indicators

Various relaxation techniques could benefit from merging with virtual reality (VR) technologies, as these technologies are easily applicable, involving, and user-friendly. To date, it is unclear which relaxation technique using biofeedback combined with VR technology is the most effective. The study aimed to compare the effectiveness of brief VR-based biofeedback-assisted relaxation techniques including electroencephalographic biofeedback, mindfulness-based biofeedback, galvanic skin response biofeedback, and respiratory biofeedback. Forty-three healthy volunteers (age 34.7 ± 7.2 years), comprising 28 (65%) women and 15 (35%) men, were enrolled in the study. All the participants were exposed to four distinct relaxation sessions according to a computer-generated random sequence. The efficacy of relaxation methods was evaluated by examining psychological, physiological, and biochemical stress indicators. All VR-based relaxation techniques reduced salivary steroid hormone (i.e., cortisol, cortisone, and total glucocorticoid) levels and increased galvanic skin response values. Similarly, all interventions led to a significantly reduced subjectively perceived psychological strain level. Three out of the four interventions (i.e., electroencephalographic, respiratory, and galvanic skin response-based biofeedback relaxation sessions) resulted in a decreased self-reported fatigue level. We suggest that newly developed VR-based relaxations techniques are potential tools for stress reduction and might be particularly suitable for individuals who are not capable of adhering to a strict and time-consuming stress management intervention schedule.

Inter-event Times Statistic in Stationary Processes: Nonlinear ARMA Modeling of Wind Speed Time Series

The random sequence of inter-event times of a level-crossing is a statistical tool that can be used to investigate time series from complex phenomena. Typical features of observed series as the skewed distribution and long range correlations are modeled using non linear transformations applied to Gaussian ARMA processes. We investigate the distribution of the inter-event times of the level-crossing events in ARMA processes in function of the probability corresponding to the level. For Gaussian ARMA processes we establish a representation of this indicator, prove its symmetry and that it is invariant with respect to the application of a non linear monotonic transformation. Using simulated series we provide evidence that the symmetry disappears if a non monotonic transformation is applied to an ARMA process. We estimate this indicator in wind speed time series obtained from three different databases. Data analysis provides evidence that the indicator is non symmetric, suggesting that only highly non linear transformations of ARMA processes can be used in modeling. We discuss the possible use of the inter-event times in the prediction task.

Pharmacologic analysis of non-synonymous coding 5-HT2A SNPs reveals alterations psychedelic drug potencies and efficacies

Serotonin (5-Hydroxytryptamine; 5-HT) 2A receptor (5-HT2AR) signaling is essential for the actions of classical psychedelic drugs. In this study, we examined whether random sequence variations in the gene (single nucleotide polymorphisms, SNPs) encoding the 5-HT2AR affect the signaling of four commonly used psychedelic drugs. We examined the in vitro pharmacology of seven non-synonymous SNPs, which give rise to S12N, T25N, D48N, I197V, A230T, A447V, and H452Y variant 5-HT2A serotonin receptors. We found that these non-synonymous SNPs exert statistically significant, although modest, effects on the efficacy and potency of four therapeutically relevant hallucinogens. Significantly, the in vitro pharmacological effects of the SNPs drug actions at 5-HT2AR are drug specific.

Optimisation of absorber parameters in the case of stochastic vibrations in a bridge with a deck platform for servicing pipelines

The paper focuses on the problem of optimising the cooperation between a dynamic vibration absorber (DVA) and a structure. The authors analyse a road beam bridge equipped with a working platform (deck) used to service pipelines installed on the structure. The paper studies the problem of choosing the optimal parameters for damping absorbers that reduce the random vibration of a beam subjected to a random sequence of moving forces with a constant velocity. The stochastic properties of the load are modelled by means of a filtering Poisson process. A single-degree-of-freedom (SDOF) absorber model with a multi-degree-of-freedom (MDOF) primary structure model are is considered.

Improved Opposition-Based Particle Swarm Optimization Algorithm for Global Optimization

Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. An efficient algorithm must have symmetry of information between participating entities. Enhancing algorithm efficiency relative to the symmetric concept is a critical challenge in the field of information security. PSO also becomes trapped into local optima similarly to other nature-inspired algorithms. The literature depicts that in order to solve pre-mature convergence for PSO algorithms, researchers have adopted various parameters such as population initialization and inertia weight that can provide excellent results with respect to real world problems. This study proposed two newly improved variants of PSO termed Threefry with opposition-based PSO ranked inertia weight (ORIW-PSO-TF) and Philox with opposition-based PSO ranked inertia weight (ORIW-PSO-P) (ORIW-PSO-P). In the proposed variants, we incorporated three novel modifications: (1) pseudo-random sequence Threefry and Philox utilization for the initialization of population; (2) increased population diversity opposition-based learning is used; and (3) a novel introduction of opposition-based rank-based inertia weight to amplify the execution of standard PSO for the acceleration of the convergence speed. The proposed variants are examined on sixteen bench mark test functions and compared with conventional approaches. Similarly, statistical tests are also applied on the simulation results in order to obtain an accurate level of significance. Both proposed variants show highest performance on the stated benchmark functions over the standard approaches. In addition to this, the proposed variants ORIW-PSO-P and ORIW-PSO-P have been examined with respect to training of the artificial neural network (ANN). We have performed experiments using fifteen benchmark datasets obtained and applied from the repository of UCI. Simulation results have shown that the training of an ANN with ORIW-PSO-P and ORIW-PSO-P algorithms provides the best results than compared to traditional methodologies. All the observations from our simulations conclude that the proposed ASOA is superior to conventional optimizers. In addition, the results of our study predict how the proposed opposition-based method profoundly impacts diversity and convergence.

The Effects of Sequence Length and Composition of Random Sequence Peptides on the Growth of E. coli Cells

We study the potential for the de novo evolution of genes from random nucleotide sequences using libraries of E. coli expressing random sequence peptides. We assess the effects of such peptides on cell growth by monitoring frequency changes in individual clones in a complex library through four serial passages. Using a new analysis pipeline that allows the tracing of peptides of all lengths, we find that over half of the peptides have consistent effects on cell growth. Across nine different experiments, around 16% of clones increase in frequency and 36% decrease, with some variation between individual experiments. Shorter peptides (8–20 residues), are more likely to increase in frequency, longer ones are more likely to decrease. GC content, amino acid composition, intrinsic disorder, and aggregation propensity show slightly different patterns between peptide groups. Sequences that increase in frequency tend to be more disordered with lower aggregation propensity. This coincides with the observation that young genes with more disordered structures are better tolerated in genomes. Our data indicate that random sequences can be a source of evolutionary innovation, since a large fraction of them are well tolerated by the cells or can provide a growth advantage.