Approved algorithmic security enhancement of stream cipher for advanced mobile communications

ABSTRACT

Confidentiality and integrity processes are based on SNOW and ZUC algorithms. These standardized algorithms are designed by the 3rd Generation Partnership Project (3GPP) for advanced mobile communication systems. Each algorithm has two S-boxes in its nonlinear layer structure. This paper proposes three different approaches to enhance the security level of both algorithms. The first approach aims to select the best combination of two S-boxes in the nonlinear part of each algorithm. Results showed that the best randomness properties are achieved by combining the Feistel structure (S1-box) and Rijndael (S2-box) in the SNOW algorithm and New Rijndael (S1-box) and Rijndael (S2-box) in the ZUC algorithm. The second approach aims to increase the nonlinearity and complexity of these algorithms by selecting a strong S-box to cascade the best-existing two S-boxes for both algorithms. The third approach is an extension of the former, based on a dynamic reform of such S-boxes as a function of the “Authentication Token” to increase the computational complexity of the upgraded two algorithms. These proposed upgrades are simulated by C language and tested successfully for their statistical properties using the standard NIST SP 800-22 test suite.     

Effective prediction and resource allocation method (EPRAM) in fog computing environment for smart healthcare system

Multimedia Tools and Applications - Recently, many concepts in technology has been changed. According to the digital transformation trends, Internet of Things (IoT) represents an interested...     

Scaling up stochastic gradient descent for non-convex optimisation

Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions and large datasets. We address the bottleneck problem arising when using both shared and distributed memory. Typically, the former is bounded by limited computation resources and bandwidth whereas the latter suffers from communication overheads. We propose a unified distributed and parallel implementation of SGD (named DPSGD) that relies on both asynchronous distribution and lock-free parallelism. By combining two strategies into a unified framework, DPSGD is able to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied for non-convex problems such as those arising in statistical modelling and machine learning. Our theoretical analysis shows that DPSGD leads to speed-up with respect to the number of cores and number of workers while guaranteeing an asymptotic convergence rate of \(O(1/\sqrt{T})\) given that the number of cores is bounded by \(T^{1/4}\) and the number of workers is bounded by \(T^{1/2}\) where T is the number of iterations. The potential gains that can be achieved by DPSGD are demonstrated empirically on a stochastic variational inference problem (Latent Dirichlet Allocation) and on a deep reinforcement learning (DRL) problem (advantage actor critic - A2C) resulting in two algorithms: DPSVI and HSA2C. Empirical results validate our theoretical findings. Comparative studies are conducted to show the performance of the proposed DPSGD against the state-of-the-art DRL algorithms.

     

A new route for the preparation of cyano‐containing poly(N‐isopropylacrylamide) microgel latex for specific immobilization of antibodies

A prepolymerization process was used to prepare functionalized poly(N‐isopropylacrylamide) latexes with surface cyano groups. The functionalized latexes prepared were characterized by FTIR, ¹H NMR, scanning electron microscopy and quasi‐elastic light scattering. In addition, the polymerization conversion and the water‐soluble polymer amounts were quantified. The polymerization conversions were found to be above 80% with 5–14 wt% of water soluble polymer formation. The immobilization of antibody (immunoglobulin) onto such cyano‐containing thermally sensitive particles, suggests the feasibility of specific dipole–dipole interactions between the cyano and hydroxyl functional groups from particle and antibody, respectively. Copyright © 2004 Society of Chemical Industry     

Sulfated Zirconia-Based Strong Solid-Acid Catalysts: Recent Progress

This review article deals with recent progress in the preparation of sulfated zirconia (SZ)-bassed, strong solid-acid catalysts, the characterization of their physicochemical properties and the evaluation of their catalytic performance in various promising applications. Strong emphasis was put on discussion of controversial issues such as the strength of acid sites, the nature of active sites, the reaction mechanism, and the role and state of supported platinum. An important part of this work was devoted to recent catalytic applications.     

Methanogenic fermentation of scots pine (Pinus sylvestris) sawdust: Enhancement by physicochemical pretreatment

The three major polymeric components of Scots Pine sawdust–lignin, hemicellulose and cellulose–represent potential substrates for methanogenic fermentation although, in the absence of physicochemical pretreatment, low digestibility was demonstrated even after protracted incubation (18 months). Acid (H₂SO₄) and alkali (NaOH) pretreatments mediated different effects although, in general, the rates and percent solubilisations increased with concentration, temperature, pressure and time, either singly or in combination. Individual methanogenic fermentations with the hydrolysates and residual solids showed that although 3.3% more methane resulted from the H₂SO₄ hydrolysate than the corresponding NaOH hydrolysate, in total, 7% more methane was generated from the two alkali fractions than from the corresponding acid fractions. The results thus exemplified that choice of a specific physicochemical strategy must be made in conjunction with the expected yield from the selected fraction(s).     

The Role of Crosslink Density in Influencing the Electrical Resistance Behaviour of Polymeric Coatings

Paint films used to protect metalic surfaces are commonly polymeric in nature. The extent of protection offered by film depends on many factors including the characteristic electrical resistance behaviou and its effect on impeding local electrochemical processes. In the present work a range of polymeric coatings have been produced with systematically varied crosslinked density using an ultra-violet light curing technique. Their electrical resistance behaviour in an environment of varying concentrations of KC1 electrolyte has been examined. It is demonstrated that there are signs of the beginnings of a mechanism changeover from “D-type” to “I-type” behaviour at higher levels of crosslink density thus giving some tenuous support to previously unproven hypotheses in this area.     

Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization

This paper presents a space vector modulation (SVM) based Direct Torque Control strategy (DTC) for induction motor (IM) in order to overcome the drawbacks of the classical DTC. SVM can reduce the high torque and flux ripples by preserving a fixed switching frequency. This technique is known by the closed loop torque SVM-DTC. Moreover, the control scheme performance is improved by inserting a second order sliding mode super twisting controller in the outer loop for speed regulation. This nonlinear technique ensures a good dynamic and high robustness against external disturbance. Furthermore, the IM energy optimization is treated in the second objective of this paper. A proposed model based loss minimization strategy is presented for efficiency optimization. This strategy chooses an optimal flux magnitude for each applied load torque. The proposed optimized SVM-DTC algorithm will be investigated by simulation and real time implementation using Matlab/Simulink with real time interface based on dSpace 1104 signal card.