Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks by Kashi Sai Prasad, E. Laxmi Lydia, M. V. Rajesh, K. Radhika, Janjhyam Venkata Naga Ramesh, N. Neelima, Srinivasa Rao Pokuri

“…The IoT network’s security can progressively become a critical concern as IoT technology obtains extensive use. …”
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Zero-day exploits detection with adaptive WavePCA-Autoencoder (AWPA) adaptive hybrid exploit detection network (AHEDNet) by Ahmed A. Mohamed, Abdullah Al-Saleh, Sunil Kumar Sharma, Ghanshyam G. Tejani

“…Additionally, a novel “Meta-Attention Transformer Autoencoder (MATA)” for enhancing feature extraction which address the subtlety issue, and improves the model’s ability and flexibility to detect new security threats, and a novel “Genetic Mongoose-Chameleon Optimization (GMCO)” was introduced for effective feature selection in the case of addressing the efficiency challenges. …”
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A novel integration of multi-stocked gated variant recurrent units and Kolmogorov-Arnold tuned deep training networks for anchoring the intrusion detection against computer attacks by M. Saritha, Saidireddy Malgireddy

“…Abstract With the explosive expansion of smart computers, there is a rapid intrusion of network attacks in the user’s personal life that intensifies the privacy and security breaches. …”
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USING SUPPORT VECTORS TO BUILD A RULE-BASED SYSTEM FOR DETECTING MALICIOUS PROCESSES IN AN ORGANISATION'S NETWORK TRAFFIC by Halyna Haidur, Sergii Gakhov, Dmytro Hamza

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A multi-model feature fusion based transfer learning with heuristic search for copy-move video forgery detection by Hessa Alfraihi, Muhammad Swaileh A. Alzaidi, Hamed Alqahtani, Abdulbasit A. Darem, Ali M. Al-Sharafi, Ahmad A. Alzahrani, Menwa Alshammeri, Abdulwhab Alkharashi

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Pseudo-Random Identification and Efficient Privacy-Preserving V2X Communication for IoV Networks by Sujash Naskar, Gerhard Hancke, Tingting Zhang, Mikael Gidlund

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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…The suggested method is appropriate for practical IoT security applications since it provides strong domain generalization and explainability while preserving computational efficiency.…”
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A Consistency-Aware Hybrid Static–Dynamic Multivariate Network for Forecasting Industrial Key Performance Indicators by Jiahui Long, Xiang Jia, Bingyi Li, Lin Zhu, Miao Wang

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A Multi-Class Intrusion Detection System for DDoS Attacks in IoT Networks Using Deep Learning and Transformers by Sheikh Abdul Wahab, Saira Sultana, Noshina Tariq, Maleeha Mujahid, Javed Ali Khan, Alexios Mylonas

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Protecting Industrial Control Systems From Shodan Exploitation Through Advanced Traffic Analysis by Sayed Reza Ghazinour Naeini, Alireza Shameli-Sendi, Masoume Jabbarifar

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A novel speaker verification approach featuring multidomain acoustics based on the weighted city-block Minkowski distance by Khushboo Jha, Sumit Srivastava, Aruna Jain

“…Access control is vital in interconnected environments like the Internet of Things, Industry 4.0, and smart connectivity, ensuring authorized access for security. Biometric-based access, particularly speaker verification (SV), enhances security with unique vocal features, offering nonintrusive authenti-cation with continuous monitoring. …”
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Post-disaster building damage assessment based on gated adaptive multi-scale spatial-frequency fusion network by Bo Yu, Yao Sun, Jiansong Hu, Fang Chen, Lei Wang

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Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei, Riad Alharbey

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A comprehensive survey on techniques, challenges, evaluation metrics and applications of deep learning models for anomaly detection by Mudita Kohli, Indu Chhabra

“…Abstract Connected devices improve life quality and generate a large amount of data which require computation and transfer; the need for security becomes a major concern with networks evolving in complexity and scale. …”
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A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks by Anubhav Kumar, Rajamani Radhakrishnan, Mani Sumithra, Prabu Kaliyaperumal, Balamurugan Balusamy, Francesco Benedetto

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Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

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Evaluating the Performance of Machine Learning Classifiers for Network Intrusion Detection: A Comparative Study Using the UNSW-NB15 Dataset by Iwan Handoyo Putro

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Smart Grid Security: Proactive Prediction of Advanced Persistent Threats by Motahareh Dehghan, Erfan Khosravain

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A speech-based convolutional neural network for human body posture classification by Abdulmohsin Husam Ali

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FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments by Haonan Peng, Chunming Wu, Yanfeng Xiao

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