Adaptive memetic method of multi-objective genetic evolutionary algorithm for backpropagation neural network

Ibrahim, Ashraf Osman; Shamsuddin, Siti Mariyam; Abraham, Ajith; Qasem, Sultan Noman

doi:10.1007/s00521-018-03990-0

Cited by 22 publications

(5 citation statements)

References 45 publications

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“…However, the proposed scheme still has some limitations that need to be addressed to improve its accuracy and reduce false positives. For future work, we plan to apply an enhanced memetic adaptive method to an on neural network model [23], to improve D3S by increasing the detection accuracy and decreasing the false alarm rate of the original scheme. In contrast, comparing the speed and computational requirements of different algorithms can be a valuable part of future work, as it can help advance the field by identifying the most efficient and effective methods for solving specific problems.…”

Section: Discussionmentioning

confidence: 99%

Detection of Management-Frames-Based Denial-of-Service Attack in Wireless LAN Network Using Artificial Neural Network

Abdallah

Hamdan

Gismalla

et al. 2023

Sensors

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Wireless Local Area Networks (WLANs) have become an increasingly popular mode of communication and networking, with a wide range of applications in various fields. However, the increasing popularity of WLANs has also led to an increase in security threats, including denial of service (DoS) attacks. In this study, management-frames-based DoS attacks, in which the attacker floods the network with management frames, are particularly concerning as they can cause widespread disruptions in the network. Attacks known as denial of service (DoS) can target wireless LANs. None of the wireless security mechanisms in use today contemplate defence against them. At the MAC layer, there are multiple vulnerabilities that can be exploited to launch DoS attacks. This paper focuses on designing and developing an artificial neural network (NN) scheme for detecting management-frames-based DoS attacks. The proposed scheme aims to effectively detect fake de-authentication/disassociation frames and improve network performance by avoiding communication interruption caused by such attacks. The proposed NN scheme leverages machine learning techniques to analyse patterns and features in the management frames exchanged between wireless devices. By training the NN, the system can learn to accurately detect potential DoS attacks. This approach offers a more sophisticated and effective solution to the problem of DoS attacks in wireless LANs and has the potential to significantly enhance the security and reliability of these networks. According to the experimental results, the proposed technique exhibits higher effectiveness in detection compared to existing methods, as evidenced by a significantly increased true positive rate and a decreased false positive rate.

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Section: Discussionmentioning

confidence: 99%

Detection of Management-Frames-Based Denial-of-Service Attack in Wireless LAN Network Using Artificial Neural Network

Abdallah

Hamdan

Gismalla

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

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“…The training information needs to be divided into K sections, each including an n/k specimen, wherein n is the initial sample amount, to begin the K-fold cross-validation operation. As a result, k-1 portions are employed in learning, whereas the residual portions are exploited in validation [43,44]. The gridsearch technique in our suggested method incorporates this significant strategy.…”

Section: B K-fold Cross-validationmentioning

confidence: 99%

Ascertaining Speech Emotion using Attention-based Convolutional Neural Network Framework

Arya,

Kohli

et al. 2023

IJACSA

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Conversation among people is a profuse form of interaction that also carries emotional information. Speech input has been the subject of numerous studies over the last ten years, and it is now crucial for human-computer connection, as well as for medical care, privacy, and stimulation. This research aims to evaluate if the suggested framework can aid in speech emotion recognition (SER) activities and determine if Convolutional Neural Network (CNN) systems are efficient for SER activities using transfer learning models on spectrogram. In this investigation, the authors present a brand-new attention-based CNN framework and evaluate its efficacy against several wellknown CNN architectures from earlier research. The effectiveness of the suggested system is assessed using the SAVEE dataset, an open-access resource for emotive speech, compared to famous CNN models like VGG16, InceptionV3, ResNet50, InceptionResNetV2, and Xception. The authors used stacked 10fold cross-validation on SAVEE for all of our trials. Amongst these CNN structures, the suggested model had the greatest accuracy (87.14%), followed by VGG16 (83.19%) and InceptionResNetV2 (82.22%). Compared to contemporary techniques, the test results and evaluation show our proposed approach to have steady and impressive results.

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“…GA is an evolutionary optimization strategy that draws inspiration from natural processes and is used in research on routing algorithms [37,38]. GA is a form of natural selection and evolutionary computing applied in global optimization [39][40][41][42]. GA has been demonstrated in theory and through experiments to be a reliable search method.…”

Section: Gamentioning

confidence: 99%

Improving Waste Management System Efficiency and Mobility with Efficient Path MANET

et al. 2021

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Waste Management System (WMS) is applied in smart cities and is supported by the Internet of Things (IoT). WMS involves several responsibilities, such as collection, disposal, and utilization of waste in relevant facilities. Efficient waste management has a considerable impact on the quality of life of citizens in smart cities. The interaction between wireless sensor networks and mobile ad-hoc networks (MANETs) with IoT provides excellent mobility for users, and reduces the deployment costs of networks. Data transfer via the intermediate connected devices must be maintained to shorten the distance between the devices. Intelligent routing algorithm is proposed to find efficient paths that comply with the WMS requirement constraints and avoid invalid paths that cause increased computation time. Chromosome intersection operation on genetic-based routing algorithm, intersection activation function, and intersection node table are proposed to avoid the similarity and redundancy of generated paths and keep the validity of the paths. This study improves the path finding, obtains good results, and increases the rate of efficient paths. Results show that the selected path is efficient in terms of distance, number of hops and number of iterations by using the proposed method. In addition, this proposed method outperforms DSR, which offers alternative paths with more efficiency.

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Adaptive memetic method of multi-objective genetic evolutionary algorithm for backpropagation neural network

Cited by 22 publications

References 45 publications

Detection of Management-Frames-Based Denial-of-Service Attack in Wireless LAN Network Using Artificial Neural Network

Detection of Management-Frames-Based Denial-of-Service Attack in Wireless LAN Network Using Artificial Neural Network

Ascertaining Speech Emotion using Attention-based Convolutional Neural Network Framework

Improving Waste Management System Efficiency and Mobility with Efficient Path MANET

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