Rocca: An Efficient AES-based Encryption Scheme for Beyond 5G

In this paper, we present an AES-based authenticated-encryption with associated-data scheme called Rocca, with the purpose to reach the requirements on the speed and security in 6G systems. To achieve ultra-fast software implementations, the basic design strategy is to take full advantage of the AES-NI and SIMD instructions as that of the AEGIS family and Tiaoxin-346. Although Jean and Nikolić have generalized the way to construct efficient round functions using only one round of AES (aesenc) and 128-bit XOR operation and have found several efficient candidates, there still seems to exist potential to further improve it regarding speed and state size. In order to minimize the critical path of one round, we remove the case of applying both aesenc and XOR in a cascade way for one round. By introducing a cost-free block permutation in the round function, we are able to search for candidates in a larger space without sacrificing the performance. Consequently, we obtain more efficient constructions with a smaller state size than candidates by Jean and Nikolić. Based on the newly-discovered round function, we carefully design the corresponding AEAD scheme with 256-bit security by taking several reported attacks on the AEGIS family and Tiaxion-346 into account. Our AEAD scheme can reach 138Gbps which is 4 times faster than the AEAD scheme of SNOW-V. Rocca is also much faster than other efficient schemes with 256-bit key length, e.g. AEGIS-256 and AES-256-GCM. As far as we know, Rocca is the first dedicated cryptographic algorithm targeting 6 systems, i.e., 256-bit key length and the speed of more than 100 Gbps.

Randomization of Clinical Trial Participants via an Integrated Web Service

Randomization is an inherent part of Randomized Clinical Trials (RCTs), typically requiring the split of participants in intervention and control groups. We present a web service supporting randomized patient distribution, developed in the context of the MyPal project RCT. The randomization process is based on a block permutation approach to mitigate the risk of various kind of biases. The presented service can be used via its web user interface to produce randomized lists of patients distributed in the various study groups, with a variant block size. Alternatively, the presented service can be integrated as part of wider IT systems supporting clinical trials via a REST interface following a micro-service architectural pattern.

A Robust and Fast Image Encryption Scheme Based on a Mixing Technique

This paper introduces a new image encryption scheme using a mixing technique as a way to encrypt one or multiple images of different types and sizes. The mixing model follows a nonlinear mathematical expression based on Cramer’s rule. Two 1D systems already developed in the literature, namely, the May-Gompertz map and the piecewise linear chaotic map, were used in the mixing process as pseudo-random number generators for their good chaotic properties. The image to be encrypted was first of all partitioned into N subimages of the same size. The subimages underwent a block permutation using the May-Gompertz map. This was followed by a pixel-based permutation using the piecewise linear chaotic map. The result of the two previous permutations was divided into 4 subimages, which were then mixed using pseudo-random matrices generated from the two maps mentioned above. Tests carried out on the cryptosystem designed proved that it was fast due to the 1D maps used, robust in terms of noise and data loss, exhibited a large key space, and resisted all common attacks. A very interesting feature of the proposed cryptosystem is that it works well for simultaneous multiple-image encryption.

Increased Cerebral Metabolic Stress Is Associated with Diminished Functional Connectivity in Pediatric Sickle Cell Anemia

Children with sickle cell anemia (SCA) experience increased metabolic stress in the brain, measured by oxygen extraction fraction (OEF); regions with the highest OEF co-localize with regions at greatest risk for stroke. Yet, SCA affects cognition independent of stroke. We aim to investigate the relationship between metabolic stress and the cognitive effects of SCA. Neurocognitive abilities emerge from functional networks ascertained using unctional connectivity MRI (rs-fcMRI), potentially allowing functional connectivity (fc) to be used as a biomarker for cognitive dysfunction in SCA. We prospectively obtained cognitive testing and brain MRIs in children with SCA (unaffected by overt stroke or vasculopathy, not chronically transfused and without history of transplant) and controls in a single center to test our hypothesis that children with SCA experiencing the greatest metabolic stress will have the greatest disruption in fc. Brain MRI measured OEF (asymmetric spin echo) and fc (resting state BOLD), and the NIH Toolbox Cognition Battery (NIHTB) and Wechsler Abbreviated Scale of Intelligence Second Edition (WASI-II) assessed cognition. OEF processing is described in Fields et al. Blood. 2019; 133(22):2436-2444. Temporal correlation of the BOLD signal between 264 gray matter (GM) regions was calculated and assembled into region x region matrices sorted by 13 pre-defined functional networks. Homotopy, a metric of global connectivity, was measured by correlating GM voxels in the right hemisphere with corresponding left voxels, and averaging across GM. Group comparisons were made with Mann-Whitney U or chi-squared tests. Object oriented data analysis (OODA), post-hoc block permutation testing (p-values corrected for false discovery rate (FDR)), and group comparison of average within network correlations compared fc between cohorts. Bivariate correlations were described with Pearson's r. Significance was specified as p-value < .05, and the Benjamini-Hochberg procedure controlled for a final FDR of 0.05 for group comparison excluding permutation testing. Table 1 describes the 55 participants. There was no difference in cognition between cohorts (Table 1). Homotopy was lower in SCA (0.336 [0.310-0.379]) compared to controls (0.381 [0.341-0.394], p = 0.023). Figure 1 illustrates cohort fc matrices. The intra-network regions demonstrate strong positive correlations and inter-network regions demonstrate lower correlations for each cohort, indicating functional network architecture is similar between cohorts. However, the magnitude of fc is reduced in SCA. Using OODA, there was a significant difference between matrices (p=.001), with SCD selectively affecting the magnitude of fc within specific networks: Salience (Sal), Fronto-Parietal (FP), Cingulo-Opercular (CO), Sensory-Motor (SM), Sensory-Motor Lateral (SM-Lat), and Auditory (Aud) networks when comparing within network Pearson's r between cohorts (Table 1), and the Sal (FDR-corrected p < .001) and SM-Lat (FDR-corrected p = .039) networks using block permutation testing. Whole brain (Wb) OEF correlated with homotopy (r = -.420, p = .002), and the average Pearson r within specific networks: Default Mode (r = -.481, p < .001), CO (r = -.537, p < .001), Sal (r = -.549, p < .001), FP (r = -.461, p < .001), SM (r = -.298, p = .029), SM-Lat (r = -.381, p = .004), Aud (r = -.437, p = .001), and Visual (r = -.344, p = .011) networks (Figure 2). Wb OEF did not correlate with the average Pearson r within the Cerebellar (p = .713), Subcortical (p = .974), Memory (p = .104), Dorsal Attention (p = .228), or Ventral Attention (p = .162) networks. We conclude that there are differences in rs-fcMRI in this cohort of children with SCA unaffected by overt stroke or vasculopathy when compared to controls even though cohort differences were not found with cognitive testing. Differences were found in higher level cortical association systems (Sal, FP and CO) that are associated with executive function, which is known to be affected by SCA. Knowing that there is regional variation in metabolic stress, as measured by OEF, within the brains of children with SCA, we found an association between OEF and fc in select networks. These data suggest that those experiencing the greatest metabolic stress have diminished connectivity within select fc networks, and that these imaging metrics may provide neuroimaging biomarkers for cognitive decline in SCA. Disclosures Fields: Proclara Biosciences: Equity Ownership. Mirro:Nous Imaging Inc: Employment. King:Incyte: Consultancy; WUGEN: Equity Ownership; Tioma Therapeutics (formerly Vasculox, Inc.):: Consultancy; RiverVest: Consultancy; Novimmune: Research Funding; Amphivena Therapeutics: Research Funding; Bioline: Consultancy; Celgene: Consultancy; Cell Works: Consultancy; Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees.

A Novel Color Image Encryption Algorithm Based on Hyperchaotic System and Permutation-Diffusion Architecture

In recent years, scholars studied and proposed some secure color image encryption algorithms. However, the majority of the published algorithms encrypted red, green and blue (called [Formula: see text], [Formula: see text], [Formula: see text] for short) components independently. In the paper, we propose a color image encryption scheme based on hyperchaotic system and permutation-diffusion architecture. The encryption algorithm utilizes a block permutation which is realized by mixing [Formula: see text], [Formula: see text], [Formula: see text] components to strengthen the dependence of each component. Besides, it can reduce time consumption. Then, the key streams generated by the hyperchaotic system are exploited to diffuse the pixels, the three components affect each other again. And in the diffusion process, we can get two totally different encrypted images even though we change the last pixel because the [Formula: see text] component is diffused in reverse order. The experimental results reveal that our algorithm possesses better abilities of resisting statistical attacks and differential attacks, larger key space, closer information entropy to 8, and faster encryption speed compared with other chaos-based color image encryption algorithms.

Cryptanalysis and Improvement of a Color Image Encryption Scheme Based on DNA Sequences and Multiple 1D Chaotic Maps

This paper presents cryptanalysis of a color image encryption scheme. DNA encoding and multiple 1D chaotic maps are used in the encryption process which increases its computational speed. The key streams generated in this scheme are dependent on secret keys, updated using the sum of pixel intensities of plain image of size [Formula: see text]. This paper analyzes the security of encryption scheme against the chosen plaintext attack and finds that only [Formula: see text] different key matrices for diffusion are possible, an equivalent version of which can be revealed with [Formula: see text] chosen plain images. Experimental results are presented to prove that equivalent diffusion keys and block permutation sequence can be effectively revealed through the attack. In addition, low sensitivity of keys towards changes in plaintext along with insecure diffusion process involved in encryption process is also reported. Finally, to remedy the shortcomings of the original encryption scheme, an enhanced encryption scheme is generated that can resist chosen/known plaintext attack while maintaining the merits of the original encryption scheme.