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 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 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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Knowledge Improved Hybrid DNN–KAN Framework for Intrusion Detection in Wireless Sensor Networks by M. Sriraghavendra, Muna Elsadig, Ines Hilali Jaghdam, S. Abdel-Khalek, B. Galeebathullah, Salem Alkhalaf

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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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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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Hybrid Big Bang-Big crunch with cuckoo search for feature selection in credit card fraud detection by Mohd Shukri Ab Yajid, Nilesh Bhosle, Gadug Sudhamsu, Ali Khatibi, Sahil Sharma, Rubal Jeet, R. Sivaranjani, A. Bhowmik, A. Johnson Santhosh

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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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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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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

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Enhancing identity and access management using Hyperledger Fabric and OAuth 2.0: A block-chain-based approach for security and scalability for healthcare industry by Shrabani Sutradhar, Sunil Karforma, Rajesh Bose, Sandip Roy, Sonia Djebali, Debnath Bhattacharyya

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PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image by Kazım Kılıç, İbrahim Alper Doğru, Sinan Toklu

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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

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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 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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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

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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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