Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

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Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach by Utathya Aich, Arghyasree Saha, Marcin Woźniak, Muhammad Fazal Ijaz, Pawan Kumar Singh

“…Using these images in the second step, two pre-trained deep learning models are implemented using transfer learning to extract features for the detection of schizophrenia. In the third step, a newly developed Average subtraction wrapper-based feature selection method has been proposed to lower the number of irrelevant features. …”
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A novel feature selection technique: Detection and classification of Android malware by Sandeep Sharma, Prachi, Rita Chhikara, Kavita Khanna

“…This work introduces a novel approach to feature selection that can discover a promising subset of features for effective malware detection. The proposed technique, Multi-Wrapper Hybrid Feature Selection Technique (MWHFST), integrates wrapper-based feature selection techniques to address the limitations of individual wrapper-based feature selection methods. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

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An Efficient Approach Based on RAE-GAMI-NET for Long Range Attack Detection on Blockchain by Vasavi Chithanuru, Mangayarkarasi Ramaiah

“…The proposed explainable neural network model includes Residual Auto Encoder (RAE) guided generalized additive models with incorporating structured interactions (RAE-GAMI-Net) for LRA detection in PoS Blockchain In this work, a wrapper-based Binary Orchard Algorithm (W-BOA) is used to find the best features to lessen the dimensionality of extracted Characteristics, and a global feature extraction has been implemented based on multi-scale Densenet (MDensenet) that assures early convergence and optimal performance by providing global optimal solution. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.…”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…Malware detection datasets often contain a huge number of features, many of which are irrelevant, noisy, and duplicated. …”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. The IDAOA serves as a wrapper-based feature selection method, optimizing the identification of the most impactful features while balancing local exploration and global exploitation. …”
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A Multi-Objective Bio-Inspired Optimization for Voice Disorders Detection: A Comparative Study by Maria Habib, Victor Vicente-Palacios, Pablo García-Sánchez

“…As early detection of voice disorders can significantly improve patients’ situation, the automated detection using Artificial Intelligence techniques can be crucial in various applications in this scope. …”
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Optimizing feature selection and deep learning techniques for precise detection of low-rate distributed denial of service (LDDoS) attack by Naeem Ali Al-Shukaili, Miss Laiha M. Kiah, Ismail Ahmedy

“…Further, this study compares two alternative feature selection strategies filter-based and wrapper-based—to see which works best for detecting these sneaky but persistent dangers. …”
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Leveraging federated learning for DoS attack detection in IoT networks based on ensemble feature selection and deep learning models by Tasneem Qasem Al-Ghadi, Selvakumar Manickam, I. Dewa Made Widia, Eka Ratri Noor Wulandari, Shankar Karuppayah

“…Detecting Denial-of-Service (DoS) attacks in IoT networks is critical for ensuring cybersecurity. …”
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Machine learning for Internet of Things (IoT) device identification: a comparative study by Hamid Tahaei, Anqi Liu, Hamid Forooghikian, Mehdi Gheisari, Faiz Zaki, Nor Badrul Anuar, Zhaoxi Fang, Longjun Huang

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A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and D... by Orhan Cicek, Yusuf Bahri Özçelik, Aytaç Altan

“…The proposed model, with its low computational complexity, successfully handles the nonlinear dynamics in C2, C3, and C4 vertebral images, enabling accurate detection of growth and developmental stages. This work represents a significant step in the detection of growth and development stages and provides a practical and effective solution for future orthodontic diagnosis.…”
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Methodology for Feature Selection of Time Domain Vibration Signals for Assessing the Failure Severity Levels in Gearboxes by Antonio Pérez-Torres, René-Vinicio Sánchez, Susana Barceló-Cerdá

“…Early failure detection in gear systems reduces unplanned downtime and associated maintenance costs in rotating machinery. …”
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