Multibyte Electromagnetic Analysis Based on Particle Swarm Optimization Algorithm

Sun, Shaofei; Cui, Xiaotong; Liang, Dong; Khan, Muhammad Saad; Fang, Xing

doi:10.3390/app11020839

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…The key principles of species progress in nature are mirrored by the cloud model because it possesses the characteristics of fragility, vulnerability, solidity, and change in the outflow of information. As a result, the discipline of transformational processing has also begun to focus on cloud architecture [27].…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

Capuchin Search Particle Swarm Optimization (CS-PSO) based Optimized Approach to Improve the QoS Provisioning in Cloud Computing Environment

Gupta,

Singh

2023

IJRITCC

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This review introduces the methods for further enhancing resource assignment in distributed computing situations taking into account QoS restrictions. While resource distribution typically affects the quality of service (QoS) of cloud organizations, QoS constraints such as response time, throughput, hold-up time, and makespan are key factors to take into account. The approach makes use of a methodology from the Capuchin Search Particle Large Number Improvement (CS-PSO) apparatus to smooth out resource designation while taking QoS constraints into account. Throughput, reaction time, makespan, holding time, and resource use are just a few of the objectives the approach works on. The method divides the resources in an optimum way using the K-medoids batching scheme. During batching, projects are divided into two-pack assembles, and the resource segment method is enhanced to obtain the optimal configuration. The exploratory association makes use of the JAVA device and the GWA-T-12 Bitbrains dataset for replication. The outrageous worth advancement problem of the multivariable capacity is addressed using the superior calculation. The simulation findings demonstrate that the core (Cloud Molecule Multitude Improvement, CPSO) computation during 500 ages has not reached assembly repeatedly, repeatedly, repeatedly, and repeatedly, respectively.The connection analysis reveals that the developed model outperforms the state-of-the-art approaches. Generally speaking, this approach provides significant areas of strength for a successful procedure for improving resource designation in distributed processing conditions and can be applied to address a variety of resource segment challenges, such as virtual machine setup, work arranging, and resource allocation. Because of this, the capuchin search molecule enhancement algorithm (CSPSO) ensures the success of the improvement measures, such as minimal streamlined polynomial math, rapid consolidation speed, high productivity, and a wide variety of people.

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Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

Capuchin Search Particle Swarm Optimization (CS-PSO) based Optimized Approach to Improve the QoS Provisioning in Cloud Computing Environment

Gupta,

Singh

2023

IJRITCC

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“…erefore, the field of evolutionary computing has also begun to focus on cloud design [8]. Song's algorithm for high-dimensional functions and nonlinear distribution particle optimization has been proposed to overcome the poor performance of particle optimization.…”

Section: Literature Reviewmentioning

confidence: 99%

An Improved Particle Swarm Optimization Algorithm and Its Application to the Extreme Value Optimization Problem of Multivariable Function

Min

2022

Computational Intelligence and Neuroscience

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It is proposed to improve the study of particle optimization and its application in order to solve the problem of inefficiency and lack of local optimization skills in the use of particle herd optimization. Firstly, the basic principle, mathematical description, algorithm parameters, and flow of the original (Particle Swarm Optimization, PSO) algorithm are introduced, and then the standard PSO algorithm is introduced; thirdly, over the last 10 years, four types of improvements have been proposed through the study of improved particle algorithms. The improved algorithm is applied to the extreme value optimization problem of multivariable function. The simulation results show that the basic (Cloud Particle Swarm Optimization, CPSO) algorithm within 500 generations has not reached convergence for 8 times, 6 times, 4 times, and 5 times, respectively. In the case of convergence, the average number of steps is much higher than ICPSO, and the improved algorithm converges completely. In terms of time performance, the convergence time of ICPSO is much better than that of CPSO algorithm. Therefore, the improved particle optimization algorithm ensures the effectiveness of the improvement measures, such as small optimization algebra, fast merging speed, high efficiency, and good population diversity.

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“…The system combines an electromagnetic leakage scanning platform and analysis methods into a single system, which can carry out all steps automatically. Most of the previous publications mainly focus on the key recovery of cryptographic algorithms, including our previous works [22,23]. As far as we know, there are seldom works on the electromagnetic leakage model of cryptographic integrated circuits to reveal the relationship between the electromagnetic leakage signal and the cryptographic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

Sun

Cui

et al. 2021

Entropy

Self Cite

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Cryptographic algorithm is the most commonly used method of information security protection for many devices. The secret key of cryptographic algorithm is usually stored in these devices’ registers. In this paper, we propose an electromagnetic information leakage model to investigate the relationship between the electromagnetic leakage signal and the secret key. The registers are considered as electric dipole models to illustrate the source of the electromagnetic leakage. The equivalent circuit of the magnetic field probe is developed to bridge the output voltage and the electromagnetic leakage signal. Combining them, the electromagnetic information leakage model’s function relationship can be established. Besides, an electromagnetic leakage model based on multiple linear regression is proposed to recover the secret key and the model’s effectiveness is evaluated by guess entropy. Near field tests are conducted in an unshielded ordinary indoor environment to investigate the electromagnetic side-channel information leakage. The experiment result shows the correctness of the proposed electromagnetic leakage model and it can be used to recover the secret key of the cryptographic algorithm.

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Multibyte Electromagnetic Analysis Based on Particle Swarm Optimization Algorithm

Cited by 6 publications

References 27 publications

Capuchin Search Particle Swarm Optimization (CS-PSO) based Optimized Approach to Improve the QoS Provisioning in Cloud Computing Environment

Capuchin Search Particle Swarm Optimization (CS-PSO) based Optimized Approach to Improve the QoS Provisioning in Cloud Computing Environment

An Improved Particle Swarm Optimization Algorithm and Its Application to the Extreme Value Optimization Problem of Multivariable Function

Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

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