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Max Schrötter, Andreas Niemann and Bettina Schnor
Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusi...
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Nikola Andelic and Sandi Baressi ?egota
This investigation underscores the paramount imperative of discerning network intrusions as a pivotal measure to fortify digital systems and shield sensitive data from unauthorized access, manipulation, and potential compromise. The principal aim of this...
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Alejandro Valencia-Arias, Juan David González-Ruiz, Lilian Verde Flores, Luis Vega-Mori, Paula Rodríguez-Correa and Gustavo Sánchez Santos
Machine learning and blockchain technology are fast-developing fields with implications for multiple sectors. Both have attracted a lot of interest and show promise in security, IoT, 5G/6G networks, artificial intelligence, and more. However, challenges ...
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Yussuf Ahmed, Muhammad Ajmal Azad and Taufiq Asyhari
In recent years, there has been a notable surge in both the complexity and volume of targeted cyber attacks, largely due to heightened vulnerabilities in widely adopted technologies. The Prediction and detection of early attacks are vital to mitigating p...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Omar Abdulkhaleq Aldabash and Mehmet Fatih Akay
An IDS (Intrusion Detection System) is essential for network security experts, as it allows one to identify and respond to abnormal traffic present in a network. An IDS can be utilized for evaluating the various types of malicious attacks. Hence, detecti...
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Dominic Lightbody, Duc-Minh Ngo, Andriy Temko, Colin C. Murphy and Emanuel Popovici
The growth of the Internet of Things (IoT) has led to a significant rise in cyber attacks and an expanded attack surface for the average consumer. In order to protect consumers and infrastructure, research into detecting malicious IoT activity must be of...
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Haedam Kim, Suhyun Park, Hyemin Hong, Jieun Park and Seongmin Kim
As the size of the IoT solutions and services market proliferates, industrial fields utilizing IoT devices are also diversifying. However, the proliferation of IoT devices, often intertwined with users? personal information and privacy, has led to a cont...
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Konstantinos Psychogyios, Andreas Papadakis, Stavroula Bourou, Nikolaos Nikolaou, Apostolos Maniatis and Theodore Zahariadis
The advent of computer networks and the internet has drastically altered the means by which we share information and interact with each other. However, this technological advancement has also created opportunities for malevolent behavior, with individual...
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Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus...
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