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crossrefFuture Internet2025-05-15Cited by 8

A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks

Anubhav Kumar, Rajamani Radhakrishnan, Mani Sumithra, Prabu Kaliyaperumal, Balamurugan Balusamy, Francesco Benedetto

The rapid expansion of network environments has introduced significant cybersecurity challenges, particularly in handling high-dimensional traffic and detecting sophisticated threats. This study presents a novel, scalable Hybrid Autoencoder–Extreme Learning Machine (AE–ELM) framework for Intrusion Detection Systems (IDS), specifically designed to operate effectively in dynamic, cloud-supported IoT environments. The scientific novelty lies in the integration of an Autoencoder for deep feature compression with an Extreme Learning Machine for rapid and accurate classification, enhanced through adaptive thresholding techniques. Evaluated on the CSE-CIC-IDS2018 dataset, the proposed method demonstrates a high detection accuracy of 98.52%, outperforming conventional models in terms of precision, recall, and scalability. Additionally, the framework exhibits strong adaptability to emerging threats and reduced computational overhead, making it a practical solution for real-time, scalable IDS in next-generation network infrastructures.

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crossrefFuture Internet2026-02-19

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Software-Defined Networking (SDN) has emerged as a fundamental architecture for future Internet systems by enabling centralized control, programmability, and fine-grained traffic management. However, the logical centralization of the SDN control plane also introduces critical vul…

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crossrefFuture Internet2026-04-27Cited by 1

Enhancing Network Intrusion Detection with Quantum Machine Learning: A Comprehensive Survey of Methods, Metrics, and Applications

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Quantum computing introduces new computational capabilities that can support advanced cybersecurity solutions when combined with machine learning. In recent years, quantum machine learning (QML) has emerged as a promising approach for enhancing network intrusion detection systems…

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crossrefFuture Internet2023-08-14Cited by 10

Enhancing Network Security: A Machine Learning-Based Approach for Detecting and Mitigating Krack and Kr00k Attacks in IEEE 802.11

Zaher Salah, Esraa Abu Elsoud

The rise in internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication networks from illegal intrusi…

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crossrefFuture Internet2023-08-19Cited by 24

An Improved Deep Learning Model for DDoS Detection Based on Hybrid Stacked Autoencoder and Checkpoint Network

Amthal K. Mousa, Mohammed Najm Abdullah

The software defined network (SDN) collects network traffic data and proactively manages networks. SDN’s programmability makes it excellent for developing distributed applications, cybersecurity, and decentralized network control in multitenant data centers. This exceptional arch…

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crossrefFuture Internet2021-04-28Cited by 260

Designing a Network Intrusion Detection System Based on Machine Learning for Software Defined Networks

Abdulsalam O. Alzahrani, Mohammed J. F. Alenazi

Software-defined Networking (SDN) has recently developed and been put forward as a promising and encouraging solution for future internet architecture. Managed, the centralized and controlled network has become more flexible and visible using SDN. On the other hand, these advanta…

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crossrefFuture Internet2024-06-05Cited by 34

Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes

Abbas Javed, Amna Ehtsham, Muhammad Jawad, Muhammad Naeem Awais, Ayyaz-ul-Haq Qureshi, Hadi Larijani

Smart home devices, also known as IoT devices, provide significant convenience; however, they also present opportunities for attackers to jeopardize homeowners’ security and privacy. Securing these IoT devices is a formidable challenge because of their limited computational resou…

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