GANs for data augmentation with stacked CNN models and XAI for interpretable maize yield prediction by Ishaan Seshukumar Pothapragada, Sujatha R

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Anonymous Authentication Scheme Based on Physically Unclonable Function and Biometrics for Smart Cities by Vincent Omollo Nyangaresi, Ahmad A. AlRababah, Ganesh Keshaorao Yenurkar, Ravikumar Chinthaginjala, Muhammad Yasir

“…In addition, the informal security analysis shows that it supports salient functional and security features such as mutual authentication, key agreement, perfect key secrecy, anonymity, and untraceability. …”
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Wireless Body Area Networks for Healthcare Applications: Protocol Stack Review by Luis Filipe, Florentino Fdez-Riverola, Nuno Costa, António Pereira

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Intrusion detection in software defined network using deep learning approaches by M. Sami Ataa, Eman E. Sanad, Reda A. El-khoribi

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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…The current evolutionary graph neural architecture search (GNAS) method mainly focuses on the topological connection and feature fusion between network layers, but it often requires a lot of computing resources, and the real-time performance of the GNN (graph neural network) model is difficult to meet the requirements when facing dynamic attacks and changing data. …”
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Network Intrusion Detection Using Knapsack Optimization, Mutual Information Gain, and Machine Learning by Akindele S. Afolabi, Olubunmi A. Akinola

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Enhancing leaf disease classification using GAT-GCN hybrid model by Shyam Sundhar, Riya Sharma, Priyansh Maheshwari, Suvidha Rupesh Kumar, T. Sunil Kumar

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Detecting malicious code variants using convolutional neural network (CNN) with transfer learning by Nazish Younas, Shazia Riaz, Saqib Ali, Rafiullah Khan, Farman Ali, Daehan Kwak

“…We further improve the detection process by employing transfer learning to automatically identify and classify malware images based on their distinctive features. Empirical results demonstrate that MVDS achieves 97.98% accuracy with high detection speed, highlighting its potential for practical implementation in strengthening network security.…”
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Adap-UIL: A Multi-Feature-Aware User Identity Linkage Framework Based on an Adaptive Graph Walk by Xiaqing Xie, Hangjiang Guo, Yueming Lu, Tianle Zhang

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Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness. by Ahmed Muqdad Alnasrallah, Maheyzah Md Siraj, Hanan Ali Alrikabi

“…Finally, a deep neural network (DNN) classifies traffic as normal or anomalous. …”
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Green IoT: how wireless sensor networks are paving the way for sustainable smart environments by Haifa Alqahtani

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PoseAlign network for hybrid structure in 2D human pose estimation by Jin Zhang, Yabo Yin, Wenzhong Yang, Doudou Ren, Danny Chen

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Towards edge-collaborative, lightweight and privacy-preserving classification framework by Jinbo XIONG, Yongjie ZHOU, Renwan BI, Liang WAN, Youliang TIAN

“…Aiming at the problems of data leakage of perceptual image and computational inefficiency of privacy-preserving classification framework in edge-side computing environment, a lightweight and privacy-preserving classification framework (PPCF) was proposed to supports encryption feature extraction and classification, and achieve the goal of data transmission and computing security under the collaborative classification process of edge nodes.Firstly, a series of secure computing protocols were designed based on additive secret sharing.Furthermore, two non-collusive edge servers were used to perform secure convolution, secure batch normalization, secure activation, secure pooling and other deep neural network computing layers to realize PPCF.Theoretical and security analysis indicate that PPCF has excellent accuracy and proved to be security.Actual performance evaluation show that PPCF can achieve the same classification accuracy as plaintext environment.At the same time, compared with homomorphic encryption and multi-round iterative calculation schemes, PPCF has obvious advantages in terms of computational cost and communication overhead.…”
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Facial Expression Recognition using Convolutional Neural Networks with Transfer Learning Resnet-50 by Annisa Ayu Istiqomah, Christy Atika Sari, Ajib Susanto, Eko Hari Rachmawanto

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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…By integrating the Federated Learning (FL) framework with cryptographic optimization techniques, FEXGBIDS addresses data silo and security challenges in the vehicular network environment. …”
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Logitwise Distillation Network: Improving Knowledge Distillation via Introducing Sample Confidence by Teng Shen, Zhenchao Cui, Jing Qi

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Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection by Hao Yan, Jianming Li, Lei Du, Binxing Fang, Yan Jia, Zhaoquan Gu

“…The rapid development of information technology has made cyberspace security an increasingly critical issue. Network intrusion detection methods are practical approaches to protecting network systems from cyber attacks. …”
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A Chaotic Maps-Based Authentication Scheme for Wireless Body Area Networks by Gaimei Gao, Xinguang Peng, Ye Tian, Zefeng Qin

“…Compared with the previous schemes, our scheme not only enjoys more security features but also has reduced computational cost of client and application provider. …”
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DSNI-Net: Forensic Network for Detecting Splicing in Salt-and-Pepper Noisy Images by Wuyang Shan, Yijie Xie, Pengbo Wang, Deng Zou, Junying Qiu, Jun Li

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Application of the Genetic Algorithm in the Network Intrusion Detection System Using NSL-KDD Data by Naglaa Ibrahim, Hana Usman

“…With the development of the Internet, technological innovation and the availability of information emerged new computer security threats. The researchers are developing new systems known as Intrusion Detection Systems IDSs for detecting the known and unknown attacks.  …”
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