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This survey systematizes the evolution of network intrusion detection systems (NIDS), from conventional methods such as signature-based and neural network (NN)-based approaches to recent integrations with large language models (LLMs). It…

Cyberattacks can cause a severe impact on power systems unless detected early. However, accurate and timely detection in critical infrastructure systems presents challenges, e.g., due to zero-day vulnerability exploitations and the…

Signature-based Intrusion Detection System (SIDS) provides a promising solution to the problem of web application security. However, the performance of the system highly relies on the quality of the signatures designed to detect attacks. A…

The proliferation of IoT systems, has seen them targeted by malicious third parties. To address this, realistic protection and investigation countermeasures need to be developed. Such countermeasures include network intrusion detection and…

Intrusion detection is an arms race; attackers evade intrusion detection systems by developing new attack vectors to sidestep known defense mechanisms. Provenance provides a detailed, structured history of the interactions of digital…

Data-driven methods have been widely used in network intrusion detection (NID) systems. However, there are currently a number of challenges derived from how the datasets are being collected. Most attack classes in network intrusion datasets…

The evolution of Internet and its related communication technologies have consistently increased the risk of cyber-attacks. In this context, a crucial role is played by Intrusion Detection Systems (IDSs), which are security devices designed…

Tables are everywhere, from scientific journals, papers, websites, and newspapers all the way to items we buy at the supermarket. Detecting them is thus of utmost importance to automatically understanding the content of a document. The…

Most research in the area of intrusion detection requires datasets to develop, evaluate or compare systems in one way or another. In this field, however, finding suitable datasets is a challenge on to itself. Most publicly available…

Besides the advantages derived from the ever present communication properties, it increases the attack surface of a network as well. As industrial protocols and systems were not designed with security in mind, spectacular attacks on…

Purveyors of malicious network attacks continue to increase the complexity and the sophistication of their techniques, and their ability to evade detection continues to improve as well. Hence, intrusion detection systems must also evolve to…

The exponential increase in academic publications has made it increasingly difficult for researchers to remain up to date and systematically synthesize knowledge scattered across vast and fragmented research domains. Literature reviews,…

Past attacks against industrial control systems (ICS) show that adversaries often target both the ICS network and the physical process to achieve potential catastrophic impact. To secure ICS, intrusion detection systems promise timely…

The escalating frequency of intrusions in networked systems has spurred the exploration of new research avenues in devising artificial intelligence (AI) techniques for intrusion detection systems (IDS). Various AI techniques have been used…

With the increasing amount of reliance on digital data and computer networks by corporations and the public in general, the occurrence of cyber attacks has become a great threat to the normal functioning of our society. Intrusion detection…

This work presents Reliable-NIDS (R-NIDS), a novel methodology for Machine Learning (ML) based Network Intrusion Detection Systems (NIDSs) that allows ML models to work on integrated datasets, empowering the learning process with diverse…

Network Intrusion Detection Systems (NIDS) have been studied for decades. Hundreds of papers have, e.g., proposed ways to enhance, harden or bypass NIDS. However, the findings of prior literature are hardly reflected in real-world…

Conventional security solutions are insufficient to address the urgent cybersecurity challenge posed by insider attacks. While a great deal of research has been done in this area, our systematic literature analysis attempts to give readers…

Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to encourage data sharing and reuse, from scientific publishers asking authors to submit data alongside manuscripts…

The evolution of the web server contents and the emergence of new kinds of intrusions make necessary the adaptation of the intrusion detection systems (IDS). Nowadays, the adaptation of the IDS requires manual -- tedious and unreactive --…