![]() ![]() Researchers of projects at the sub-Antarctic Prince Edward Islands are increasingly considering geospatial data as an essential component in answering scientific questions. Furthermore, although the paper does present a set of suggestions about future inductive directions, it leaves the reader free to derive additional insights about how to develop intelligent-based systems to counter current and future network attacks. This research provides a rich source of references for scholars seeking to determine their scope of research in this field. The main components of any intelligent-based system are the training datasets, the algorithms, and the evaluation metrics these were the main benchmark criteria used to assess the intelligent-based systems included in this research article. This was the main motivation behind this research, which evaluates contemporary intelligent-based research directions to address the gap that still exists in the field. This is because some intelligent-based approaches lack essential capabilities that render them reliable systems that are able to confront different types of network attacks. However, although such techniques have proved useful within specific domains, no technique has proved useful in mitigating all kinds of network attacks. In the literature, there are various descriptions of network attack detection systems involving various intelligent-based techniques including machine learning (ML) and deep learning (DL) models. ![]() Network attack detection is an active area of research in the community of cybersecurity. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading to serious consequences. The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. ![]()
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