Currently, the Intrusion Detection System (IDS) is attracting both the commercial companies and theresearch community as IDS is playing an increasingly important role in most network systems to detect and blockpossi-ble attacks. This paper aims to present a general view of the state-of-the-art of the IDS, based on a proposedtaxonomy so that the researchers can quickly become familiar with the essential aspects of the intrusion detection techniques. The taxonomy includes reclassifying IDSs according to multiple bases, e.g., IDS’ data source,the detection method, and others. Also, comparisons among different detection approaches and various datacollection techniques are tabulated. Besides, the paper exhibits the taxonomy of anomaly-based IDSs classifyingthe promising techniques and summarizing the merits of the most recent anomaly-based techniques as a table.Furthermore, it deliberates the IDSs through various applications, like data centers, backbone, Fog, and CloudComputing, and IoT models, in addition to the most common prevailing models. Subsequently, multiple metricsand the datasets frequently used to assess the IDS are described concisely. Finally, the requirements and challengesof contemporary IDSs are mapped.
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