Novel Federated Graph Contrastive Learning for IoMT Security: Protecting Data Poisoning and Inference Attacks by Amarudin Daulay, Kalamullah Ramli, Ruki Harwahyu, Taufik Hidayat, Bernardi Pranggono

“…In this paper, we propose FedGCL, a secure and efficient FL framework integrating contrastive graph representation learning for enhanced feature discrimination, a Jain-index-based fairness-aware aggregation mechanism, an adaptive synchronization scheduler to optimize communication rounds, and secure aggregation via homomorphic encryption within a Trusted Execution Environment. …”
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Bridging Explainability and Security: An XAI-Enhanced Hybrid Deep Learning Framework for IoT Device Identification and Attack Detection by Prabhav Jain, Anshika Rathour, Aashima Sharma, Gurpal Singh Chhabra

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Secure internet of medical things based electronic health records scheme in trust decentralized loop federated learning consensus blockchain by Megha Kuliha, Sunita Verma

“…The proposed classification model demonstrates high flexibility and scalability, making it applicable to a wide range of network architectures for various computer vision tasks. …”
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Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs by Shiyun Li, Omar Dib

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Horizontal and Vertical Part-Wise Feature Extraction for Cross-View Gait Recognition by Md. Zasim Uddin, Kamrul Hasan, Md Atiqur Rahman Ahad, Fady Alnajjar

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Spatial correlation guided cross scale feature fusion for age and gender estimation by Shiyi Jiang, Qing Ji, Hukui Shi, Che Chen, Yang Xu

“…Abstract To address the challenges of age and gender recognition in uncontrolled scenarios with facial absence or severe occlusion, this paper proposes a Spatial Correlation Guided Cross Scale Feature Fusion Network (SCGNet). The proposed method specifically tackles the limitations of existing approaches that heavily rely on facial features, which become unreliable under partial/complete occlusion scenarios. …”
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A Deep Learning Approach Based on Interpretable Feature Importance for Predicting Sports Results by Bendiaf Messaoud, Khelifi Hakima, Mohdeb Djamila, Belazzoug Mouhoub, Saifi Abdelhamid

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ST-CFI: Swin Transformer with convolutional feature interactions for identifying plant diseases by Sheng Yu, Li Xie, Liang Dai

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Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

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OPTICALS: A Novel Framework for Optimizing Predictive Trading Indicators in Cryptocurrency Using Advanced Learning Simulations by Hasib Shamshad, Fasee Ullah, Syed Adeel Ali Shah, Muhammad Faheem, Beena Shamshad

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Location deployment of depots and resource relocation for connected car-sharing systems through mobile edge computing by Xiaolu Zhu, Jinglin Li, Zhihan Liu, Fangchun Yang

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Node Classification Based on Kolmogorov-Arnold Networks by YUAN Lining, FENG Wengang, LIU Zhao

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Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure by Md Junayed Hossain, Khorshed Alam, Md Fahad Monir, Md Mozammal Hoque, Tarem Ahmed

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Blockchain enhanced distributed denial of service detection in IoT using deep learning and evolutionary computation by V. V. S. H. Prasad, Swathi Sowmya Bavirthi, C. S. S. Anupama, E. Laxmi Lydia, K. Sathesh Kumar, Khalid Ammar, Mohamad Khairi Ishak

“…The IoT devices are said to be resource-constrained with computing resources and restricted memory. As a developing technology, BC holds the possibility of resolving security problems in IoT. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

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Graph neural network-tracker: a graph neural network-based multi-sensor fusion framework for robust unmanned aerial vehicle tracking by Karim Dabbabi, Tijeni Delleji

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Secret Key Generation Driven by Attention-Based Convolutional Autoencoder and Quantile Quantization for IoT Security in 5G and Beyond by Anas Alashqar, Ehsan Olyaei Torshizi, Raed Mesleh, Werner Henkel

“…Physical-layer secret key generation (PSKG) has emerged as a promising technique for enhancing wireless security in Internet of Things (IoT) networks by exploiting the reciprocity of uplink and downlink channels. …”
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Synthetic biology meets neuromorphic computing: towards a bio-inspired olfactory perception system by Kevin Max, Larissa Sames, Shimeng Ye, Jan Steinkühler, Federico Corradi

“…We propose a hybrid system of synthetic sensory neurons that provides three key features: (a) receptor-gated ion channels, (b) interface between synthetic biology and semiconductors and (c) event-based encoding and computing based on spiking networks. …”
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A correlation-based binary particle swarm optimization method for feature selection in human activity recognition by Huaijun Wang, Ruomeng Ke, Junhuai Li, Yang An, Kan Wang, Lei Yu

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MACHINE LEARNING BASED STRATEGY FOR MITM ATTACK MITIGATION UTILIZING HYBRID FEATURE SELECTION by Pratik Kumar Swain, Suneeta Satpathy, Srinivasa Rao Pokuri

“…Effective detection techniques are necessary due to the considerable threat posed by Man-in-the-Middle (MITM) attacks to network security. This study integrates machine learning classification, dimensionality reduction, and hybrid feature selection to present a novel approach for MITM threat identification. …”
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