Intelligent system for IoT botnet detection using SVM and PSO optimization

Salam, M.A.

doi:10.54216/jisiot.030203

Cited by 6 publications

(3 citation statements)

References 18 publications

(23 reference statements)

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“…e PSO algorithm has the characteristics of simple implementation, high precision, and fast convergence speed. It has good applicability in the solution process, so it has attracted the attention of many researchers [11][12][13].…”

Section: Principle Of Particle Swarm Algorithmmentioning

confidence: 99%

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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Neuromuscular control refers to the reflexes of nerves that affect muscle balance and function. In addition, there are interactions between joint structure, muscle function, and the central nervous system. In the integration with other intelligent control methods and optimization algorithms, such as fuzzy control/expert verification and genetic algorithm, it provides nonparametric object models, optimization parameters, reasoning models, and fault diagnosis. The central nervous system is the main research object of neuromuscular control. Martial arts often cause injuries or affect the progress of martial arts because of some irregular movements. Chinese traditional martial arts is another name for “martial arts” in the late Qing Dynasty in China. It is mainly reflected in the individual’s application and attainments in martial arts traditional teaching methods and personal cultivation. Therefore, this paper proposes an analysis of the influence of sports biomechanics on martial arts sports and comprehensive neuromuscular control in the context of artificial intelligence. In this paper, the specific research of Wushu sports is carried out mainly in two aspects: sports biomechanics and neuromuscular control. It uses a variety of algorithms, successively using particle swarm algorithm, neural network structure, fitness function, and so on. This paper compares and analyzes their accuracy and then selects the optimal algorithm. It then conducts experimental research on the martial arts movements of professional martial arts Sanda players. The final experimental conclusion shows that, regarding lower limb selective response time and the middle left lower limb prereaction time (L-PMT) of the elite athlete group and the ordinary athlete group, the average movement value of the elite group of 2.336 is significantly greater than that of the ordinary group of 1.938. This shows that, within a certain range, the larger the knee angle and the smaller the hip angle, the stronger the ability to buffer the impact of the ground, without causing greater damage to the muscles and joints.

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Section: Principle Of Particle Swarm Algorithmmentioning

confidence: 99%

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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“…It also optimized the hyperparameters of the one-class support vector machine and identified the features that best described the IoT zombie network problem. Salam et al [21] proposed an improved method for detecting IoT zombie networks by using particle swarm optimization to adjust the hyperparameters of ONE-SVM. This method outperformed existing algorithms in terms of false positive rate, true positive rate, and G-mean value across all categories of IoT devices.…”

Section: Related Workmentioning

confidence: 99%

IoT Botnet Attack Detection Model Based on DBO-Catboost

2023

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With the widespread adoption of Internet of Things (IoT) technology, the increasing number of IoT devices has led to a rise in serious network security issues. Botnets, a major threat in network security, have garnered significant attention over the past decade. However, detecting these rapidly evolving botnets remains a challenge, with current detection accuracy being relatively low. Therefore, this study focuses on designing efficient botnet detection models to enhance detection performance. This paper improves the initial population generation strategy of the Dung Beetle Optimizer (DBO) by using the centroid opposition-based learning strategy instead of the original random generation strategy. The improved DBO is applied to optimize Catboost parameters and is employed in the field of IoT botnet detection. Performance comparison experiments are conducted using real-world IoT traffic datasets. The experimental results demonstrate that the proposed method outperforms other models in terms of accuracy and F1 score, indicating the effectiveness of the proposed approach in this field.

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“…Particle swarm optimization (PSO) is an evolutionary algorithm whose main goal is to graph the irregular behaviour of birds to realize intelligent simulation of the foraging process [22][23][24]. As shown in Fig.…”

Section: Improvement Of the Hadoop Resource Scheduling Algorithmmentioning

confidence: 99%

Performance optimization of computing task scheduling based on the Hadoop big data platform

Hei

2022

Neural Comput & Applic

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Hadoop, a distributed computing framework that can efficiently process large-scale datasets, has been used by an increasing number of organizations as the basic computing framework to build cloud computing platforms. Improving its execution efficiency is a hot research direction in the industry, and the scheduling problem is a key factor affecting the execution efficiency of Hadoop. It is very important to identify its shortcomings and improve them. This paper examines and analyses the optimization of computing task scheduling performance based on the Hadoop big data platform. This paper first analyses Hadoop big data processing. Hadoop has high scalability. Computing nodes can be added at any time, and they can participate in cluster work through simple configuration. The paper discusses the improvement in the Hadoop resource scheduling algorithm. The task scheduling algorithm in the Hadoop-based data task localization proposed in this paper is compared with the default algorithm used in the Hadoop task scheduling algorithm. The former shows better local data in all four jobs, there are more data localization tasks, and the expected goal is achieved. The effectiveness of the algorithm is verified, and the performance is improved by 30%.

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Intelligent system for IoT botnet detection using SVM and PSO optimization

Cited by 6 publications

References 18 publications

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

IoT Botnet Attack Detection Model Based on DBO-Catboost

Performance optimization of computing task scheduling based on the Hadoop big data platform

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