Permutation Technique Research Articles

Universal Chosen-Ciphertext Attack for a Family of Image Encryption Schemes

In recent decades, there has been considerable popularity in employing nonlinear dynamics and permutation-substitution structures for image encryption. Three procedures generally exist in such image encryption schemes: the key schedule module for producing encryption elements, permutation for image scrambling and substitution for pixel modification. This paper cryptanalyzes a family of image encryption schemes that adopt pixel-level permutation and modular addition-based substitution. The security analysis first reveals a common defect in the studied image encryption schemes. Specifically, the mapping from the differentials of the ciphertexts to those of the plaintexts is found to be linear and independent of the key schedules, permutation techniques and encryption rounds. On this theory basis, a universal chosen-ciphertext attack is further proposed. Experimental results demonstrate that the proposed attack can recover the plaintexts of the studied image encryption schemes without a security key or any encryption elements. Related cryptographic discussions are also given.

Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications

The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality. Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques.

Satellite Image Multi-Frame Super Resolution Using 3D Wide-Activation Neural Networks

The small satellite market continues to grow year after year. A compound annual growth rate of 17% is estimated during the period between 2020 and 2025. Low-cost satellites can send a vast amount of images to be post-processed at the ground to improve the quality and extract detailed information. In this domain lies the resolution enhancement task, where a low-resolution image is converted to a higher resolution automatically. Deep learning approaches to Super Resolution (SR) reached the state-of-the-art in multiple benchmarks; however, most of them were studied in a single-frame fashion. With satellite imagery, multi-frame images can be obtained at different conditions giving the possibility to add more information per image and improve the final analysis. In this context, we developed and applied to the PROBA-V dataset of multi-frame satellite images a model that recently topped the European Space Agency’s Multi-frame Super Resolution (MFSR) competition. The model is based on proven methods that worked on 2D images tweaked to work on 3D: the Wide Activation Super Resolution (WDSR) family. We show that with a simple 3D CNN residual architecture with WDSR blocks and a frame permutation technique as the data augmentation, better scores can be achieved than with more complex models. Moreover, the model requires few hardware resources, both for training and evaluation, so it can be applied directly on a personal laptop.

Genetic Variability in the microRNA Binding Sites of BMPR1B, TGFBR1, IQGAP1, KRAS, SETD8 and RYR3 and Risk of Breast Cancer in Colombian Women.

BackgroundGenetic variants in microRNA (miR) binding sites affect the regulation of miR-dependent gene expression and have been linked to the risk of a variety of cancers including breast cancer (BC). Most BC risk variants had been identified in women of European and Asian ancestry, but genetic data for Hispanic women are scarce. Here, we investigate the association between six variants in miR binding sites and BC risk in Colombian women.MethodsWe genotyped miR binding site variants in the BMPR1B, TGFBR1, IQGAP1, KRAS, SETD8 and RYR3 genes in 1022 BC cases and 1023 controls from the Colombian breast cancer case–control (Col-BCCC) study using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Multiple logistic regression and permutation techniques were applied to assess the association between genetic variants and BC risk.ResultsWe found no evidence of association between any of the six miR binding site variants and overall or estrogen receptor subtype-specific BC risk in Colombian women.ConclusionOur findings may point to ethnic differences in the association between genetic variability in miR binding sites and breast cancer risk.

Connectivity detection in application to spike-wave discharge study

In our study, we compare three popular approaches to directed coupling analysis, in particular transfer entropy and two types of Granger causality, applied to real data from genetic absence epilepsy rats. We have chosen the channels for which the coupling architecture is already well known from previous studies. Recordings from 5 WAG/Rij rats of 8 hours duration with at least 28 spontaneous seizures of length not less than 6 s in each recording were studied. To test results for significance, surrogate signals based on series permutation technique were constructed. Connectivity development in time was investigated by considering six two-second intervals before, during and after the seizure. Our outcomes showed large differences between studied approaches, while all of them exploit the same general idea. Transfer entropy demonstrated the smallest number of significant couplings throughout all three considered measures, while the linear Granger causality showed the largest number of them. This indicates that transfer entropy is the most conservative measure and the least sensitive one. Its sensitivity is affected by insufficient series length. The linear Granger causality is likely to demonstrate insufficient specificity.

Uniform augmented q-level designs

In many practical applications, follow-up experimental designs are commonly used to explore the relationship between inputs and outputs steps by steps. As some additional resources could be available to the experimenter after the first step, some additional runs or factors may be added in the follow-up stage. The issue of uniform augmented q-level designs is investigated in this paper. Using the level permutation technique, the uniformity of augmented q-level designs is discussed under the average mixture discrepancy, and new lower bounds of average mixture discrepancy for augmented designs are obtained, which can be served as the benchmark for searching uniform augmented designs. Numerical examples show that the uniform augmented designs can be constructed with high efficiency.

Efficient image encryption scheme based on generalized logistic map for real time image processing

In this era of the information age with digitalization, the transmission of sensitive real-time image information over insecure channels is highly-likely to be accessed or even attacked by an adversary. To prevent such unauthorized access, cryptography is being used to convert sensitive information in real-time images into unintelligible data. Most of the time, schemes are proposed with a high level of security. However, the challenge always remains the slower speeds due to their high complexity which makes them unusable in the applications of real-time images. In this paper, an efficient image encryption algorithm has been developed and tested for real-time images. The proposed scheme makes use of encryption with an efficient permutation technique based on a modular logistic map to bring down the size of the chaotic value vector, required to permute real-time image. We show that an efficient permutation is obtained using only $$\sqrt{N}$$ chaotic numbers for a square image with 3N pixels (N Pixels in each color bit plane). The algorithm makes use of a 192-bit key; divided into smaller blocks and each block selected chaotically to diffuse the pixel using multiple XOR operations. The experimental analysis reveals that the proposed algorithm is immune to various statistical and differential attacks such as entropy, histogram analysis, spectral characteristic analysis, etc. A comparison of the proposed scheme with some state-of-the-art techniques show that it performs better, and as such, can be utilized for efficient real-time image encryption.

Fast and Efficient Image Encryption Algorithm Based on Modular Addition and SPD.

Bit-level and pixel-level methods are two classifications for image encryption, which describe the smallest processing elements manipulated in diffusion and permutation respectively. Most pixel-level permutation methods merely alter the positions of pixels, resulting in similar histograms for the original and permuted images. Bit-level permutation methods, however, have the ability to change the histogram of the image, but are usually not preferred due to their time-consuming nature, which is owed to bit-level computation, unlike that of other permutation techniques. In this paper, we introduce a new image encryption algorithm which uses binary bit-plane scrambling and an SPD diffusion technique for the bit-planes of a plain image, based on a card game trick. Integer values of the hexadecimal key SHA-512 are also used, along with the adaptive block-based modular addition of pixels to encrypt the images. To prove the first-rate encryption performance of our proposed algorithm, security analyses are provided in this paper. Simulations and other results confirmed the robustness of the proposed image encryption algorithm against many well-known attacks; in particular, brute-force attacks, known/chosen plain text attacks, occlusion attacks, differential attacks, and gray value difference attacks, among others.

Full C-Band 3060-km DMD-Unmanaged 3-Mode Transmission With 40.2-Tb/s Capacity Using Cyclic Mode Permutation

We have achieved the longest three mode-multiplexed full C-band transmission yet attained over 3060 km. In wideband mode-multiplexed transmission over weakly-coupled fewmode fibers (FMFs), the width of signal impulse responses is dependent on wavelength, and also exhibits a linear growth with increased transmission distance because of the presence of differential mode delay (DMD). Those properties are technically challenging issues for future deployable space division multiplexing (SDM) transport systems since they make a system design complicated, especially for terrestrial FMF transmission links. In this article, we describe how we applied a cyclic mode permutation (CMP) technique to achieve wideband long-haul FMF transmission where spatial channels are cyclically interchanged in each span to suppress DMD-induced pulse broadening. The CMP technique enabled DMD-unmanaged long-haul transmission across 4.4-THz optical bandwidth over two-mode FMF whose DMD varied in the range from 33.7-44.3 ps/km, resulting in 3060-km FMF transmission with a net capacity of 40.2 Tb/s.

A Hybrid Security System Based on Bit Rotation and Chaotic Maps

Background: This paper presents an image security system by combining bit rotation with block based chaotic maps cryptography. Methods: The system uses permutation technique that divides the image into blocks before applying right/left rotation of bits to the pixel values based on a randomly generated key. Then, the image blocks are fused together. A scrambling operation followed by chaotic map is applied on the rotated image to diffuse the image pixels using another randomly generated key. The chaotic map scatters all the pixel positions in the image. The decryption is the complete reversal operation of the encryption process. Results & Conclusion: The performance of the proposed technique is evaluated using several metrics: Histograms of both original and cipher images, correlation of adjacent pixels and correlation between the original and cipher images, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR). The results indicate a very secure technique to protect all types of images.

A Heretic in the Schoenberg Circle: Roberto Gerhard's First Engagement with Twelve-Tone Procedures inAndantino

AbstractShortly before finishing his studies with Arnold Schoenberg, Roberto Gerhard composedAndantino, a short piece in which he used for the first time a compositional technique for the systematic circulation of all pitch classes in both the melodic and the harmonic dimensions of the music. He modelled this technique on the tri-tetrachordal procedure in Schoenberg's Prelude from the Suite for Piano, Op. 25 but, unlike his teacher, Gerhard treated the tetrachords as internally unordered pitch-class collections. This decision was possibly encouraged by his exposure from the mid-1920s onwards to Josef Matthias Hauer's writings on ‘trope theory’. Although rarely discussed by scholars,Andantinooccupies a special place in Gerhard's creative output for being his first attempt at ‘twelve-tone composition’ and foreshadowing the permutation techniques that would become a distinctive feature of his later serial compositions. This article analysesAndantinowithin the context of the early history of twelve-tone music and theory.

GATRA DALAM BAHASA INDONESIA

[Title: Phrase in Indonesian Language] Indonesian language has a very important position in the Republic of Indonesia. The first position as the national language (October 28, 1928) and the second position as the state language (Chapter XV, article 36 of the 1945 Constitution). The development and founding of Indonesian language is continuously carried out in various ways. Phrase research as one of the elements in the sentence is a real form in the context of developing and fostering Indonesian language. This study aims to describe phrase in Indonesian which includes the notion of phrase, characteristics of phrase, and syntactic functions occupied by phrase. The theory used in this research is Structural theory developed by Ferdinand de Saussure. His views on language as the object of research can be concluded in the form of dichotomies as follows: (1) diachronic study and synchronic analysis, (2) langue and parole, (3) significant and signified, (4) syntagmatic relationships and paradigmatic relationships. Data was collected by observation / observation method which was assisted by note-taking techniques. Data were analyzed by distribution method and synchronous descriptive method which was assisted by substitution and permutation techniques. The presentation of the results of the analysis was done by informal methods with inductive and deductive techniques.

An Analysis of Commissive Speech Act Used by The Shopping Hosts of MNC Shop

This research focuses on the use of commissive speech act used by the shopping hosts of MNC Shop. The source of data is taken from the advertisements of household appliances, such as frying pan, rice cooker, vacuum cleaner, etc which are broadcasted in December 2018. The purposes of the research are to identify and to explain the form and the pattern as well as the function of the commissive speech acts used by the shopping hosts. This research uses qualitative approach. The data are collected by using observational method followed by recording and note-taking technique. Then, the data are analyzed by using pragmatic identity method and distributional method with deletion and permutation technique. The theory of form and pattern of the commissive speech act are based on Alwi's and Putrayasa's theory. Meanwhile the theory of its function is taken from Yule's and Ibrahim's theory. From the analysis, it is found that the commissive speech acts in the advertisement can be uttered in the form of declarative, interrogative and exclamative. The pattern can be in the form of normal sentence (subject preceding the predicate then followed by the object) or in the form of inverted sentence (the inversion of normal pattern) which the predicate preceding the subject, etc. In terms of its functions, the commissive speech acts can be used to promise, to guarantee and to convince.

An efficient spatiotemporal chaotic image cipher with an improved scrambling algorithm driven by dynamic diffusion phase

In recent years, with the rapid development of chaotic technology, many chaotic image cryptosystems based on pixel/bit-level techniques have been investigated. However, the drawbacks of a cryptosystem are as follows: (1) the security and efficiency are merely based on an investigation into standard test images and are not suitable for certain unique images in which the existence of “1s” or “0s” is significant; (2) the processing of bits requires more chaotic variables that elevate the computational complexity; (3) computational redundancy occurs when encrypting certain unique images. The first comprehensive analysis of different types of existing bit/pixel-level permutation techniques is carried out to show the inapplicability of such algorithms for popular cloud computing technology. To address the aforementioned security pitfalls of the state-of-the-art approaches and promote efficiency, an improved scrambling algorithm (ISA) and a reverse diffusion based on a dynamic keystream allocation strategy (DKAS) have been proposed. The present study adopts a spatiotemporal mixed linear-nonlinear coupling with the logistic-sine system (SMLNLC-LSS) for chaotic orbit generation. This system uses coveted cryptographic properties contrasted with the existing chaotic systems. The employed strategies such as ISA and reverse diffusion strongly enhance the relationship between the plaintext and encryption process to fortify the breaking of the proposed algorithm under known attacks. Because the ISA and DKAS mechanism share the same keystream, the efficiency of the proposed algorithm is effectively improved. Extensive security evaluation methods such as statistical, sensibility, visual-assessment, and efficiency analyses were imposed on the proposed methodology. The corresponding results accentuate the efficiency of the image cryptosystem while maintaining the superior security performance provided by the assurance of the desirable cryptographic properties.

The Use of the Evenness of Eigenvalues of Similarity Matrices to Test for Predictivity of Ecosystem Classifications

The use of the evenness (E(λ)) of the eigenvalues of similarity matrices corresponding to different hierarchical levels of ecosystem classifications, is suggested to test correlation (or predictivity) between biological communities and environmental factors as one alternative of analysis of variance (parametric or non-parametric). The advantage over traditional methods is the fact that similarity matrices can be obtained from any kind of data (mixed and missing data) by indices such as those of Goodall and Gower. The significance of E(λ) is calculated by permutation techniques. One example of application of E(λ) is given by a data set describing plant community types (beech forests of the Italian peninsula).

Semi-parametric analysis of overdispersed count and metric data with varying follow-up times: Asymptotic theory and small sample approximations.

Count data are common endpoints in clinical trials, for example magnetic resonance imaging lesion counts in multiple sclerosis. They often exhibit high levels of overdispersion, that is variances are larger than the means. Inference is regularly based on negative binomial regression along with maximum‐likelihood estimators. Although this approach can account for heterogeneity it postulates a common overdispersion parameter across groups. Such parametric assumptions are usually difficult to verify, especially in small trials. Therefore, novel procedures that are based on asymptotic results for newly developed rate and variance estimators are proposed in a general framework. Moreover, in case of small samples the procedures are carried out using permutation techniques. Here, the usual assumption of exchangeability under the null hypothesis is not met due to varying follow‐up times and unequal overdispersion parameters. This problem is solved by the use of studentized permutations leading to valid inference methods for situations with (i) varying follow‐up times, (ii) different overdispersion parameters, and (iii) small sample sizes.

Effects of Climate Change on Soil Erosion Risk Assessed by Clustering and Artificial Neural Network

The erosivity index, as a combination of the Fournier index (FI) and the Bagnouls–Gaussen aridity index (BGI), has been suggested to assess soil erosion risk. It can be easily calculated from meteorological data, i.e., precipitation and temperature. As an example application, data from 55 meteorological stations in Turkey corresponding to a period of 39 years from 1975 to 2013 are considered herein. The stations were classified using cluster analysis to obtain a zonation of Turkey based on EI yearly averages. Clustering techniques were applied to a similarity matrix between stations obtained based on the complement of the probability of the similarity ratio index. Four clusters were defined according to the maximal evenness of the eigenvalues of the within each cluster similarity matrices corresponding to different hierarchical levels of the dendrograms. The probability of similarity was calculated using a permutation technique. Time series of the EI of the clusters were used to predict their annual average values for the years from 2014 to 2040 using a multilayer back-propagation neural network (MLPBP-NN). The results showed that the four clusters represent a gradient of increasing EI. The clusters corresponding to northern and central Turkey have lower EI values and EI variability than those for southern and western Turkey. The results of the MLPBP-NN predict that the erosion risk will increase for all zones, but with high increments in southern and western Turkey. Therefore, the regions corresponding to these clusters should be subjected to detailed soil erosion risk analysis.

Multichannel Cooperative Spectrum Sensing That Integrates Channel Decoding With Fusion-Based Decision

This paper considers coded multichannel cooperative spectrum sensing (MC-CSS) employing local Neyman–Pearson testing at each sensor and channel decoding integrated with fusion-based decision. A joint multichannel decoding and decision fusion (JMCDDF) algorithm for performing a likelihood ratio test at the fusion center is derived based on the belief propagation technique. For benchmark comparison, we also derive the analytical performance of MC-CSS with error-free reporting channels that do not require channel coding, employing equal decision thresholds at each sensor. Using the JMCDDF algorithm, we compare the performance between uncoded and coded MC-CSS schemes when applying low-density parity-check (LDPC) codes in the presence of reporting channel errors. Monte–Carlo simulation results show considerable performance gains when using the proposed coded MC-CSS schemes. A 3-dB saving in link budget can be achieved by such coded MC-CSS schemes with a short (3, 6) regular LDPC code of codeword length $n_c=\text{200}$ , over uncoded MC-CSS. Finally, it is shown that in some cases, protecting the primary user (PU) channels by using variable nodes of higher degrees improves the performance. To equalize the performance for all sensed PU channels, we introduce a simple permutation technique, where, in each transmission, different variable nodes are used to protect local decisions.

OA072] Per-voxel cox regression with interaction terms

Purpose Image based data mining (IBDM) is a novel technique in which dose response relationships are extracted from routine clinical data by relating the dose at each voxel in the planned dose to the eventual outcome for the patient. In IBDM many patients are registered to a reference patient to spatially normalise their dose distributions for analysis, eliminating the need for clinician contours and removing assumptions implicit in DVH based analyses. Recently, IBDM has been used to identify a dose sensitive region in the heart where patients receiving excess dose have poorer overall survival [1] . Methods In this work, a subset (n = 872) of the cohort of patients in [1] is used, but a more sophisticated IBDM technique is applied. A Cox regression, considering tumour size, age, performance status, dose and a dose-PS interaction is calculated in each voxel of the planned dose distribution. Performance status is binarised using a threshold of PS > = 1 to account for inaccuracy in its determination. This analysis leads to a map of hazard ratio across the reference patient anatomy. Statistical significance is assessed using a permutation test in which only survival labels are permuted. Results When performing the analysis with an interaction between performance status and dose present in the Cox model, a region is identified in the base of the heart where excess dose is detrimental to survival. This region overlaps with that found by other analyses, and suggests that patients with a performance status of 2 or greater suffer a more profound effect from dose in this region. In the present analysis statistical significance is not reached in any voxel for either the dose, PS or dose-PS interaction. Conclusions A region in the base of the heart is identified, consistent with other analyses, in which excess dose is related to poorer overall survival, particularly for those patients with poor performance. Statistical significance may be reached by including more data, or modifying the permutation technique.

KATA TANYA DALAM KONSTRUKSI INTEROGATIF BAHASA MANDAILING

This study discusses the polar interrogative construction in Mandailing. This study aims to analyze the form of interrogative in Mandailing. The research data is a mandailing sentence that comes from related literature on interrogative. This research employs questions words which of the thoughts of foreign and Indonesian linguists. The research method used is descriptive method which employs substitution, permutation, and reference techniques. The result of this research shows that: Question words as interrogative markers can indicate different interrogative contruction types. Key words : question words, interrogative construction, rhetoric interrogative