## 1 Introduction
Consequently, there is an urgent need for comprehensive IoT/IIoT-specific datasets containing not only network-related information (e.g., packet-level information and flow-level information) but also events reflecting multiple benign and attack scenarios from current IoT/IIoT network environments, sensor measurement data, and information related to the behaviour of the IoT/IIoT devices deployed within the IoT/IIoT network for efficient and effective training and evaluation of AIDSs suitable for IoT/IIoT networks. Towards this direction, the recent work of [4] has proposed, for the first time, to the best of our knowledge, a new dataset that includes events of a variety of IoT-related attacks and legitimate scenarios, IoT telemetry data collected from heterogeneous IoT/IIoT data sources, network traffic of IoT/IIoT network, and audit traces of operating systems [4]. Therefore, it is clear that more comprehensive IoT/IIoT-specific datasets including events reflecting multiple benign and attack scenarios, sensor measurement data, network-related information, and information related to the behaviour of the IoT/IIoT devices are required to be generated and become publicly available to the research community so as to fill this significant research gap of lack of benchmark IoT/IIoT datasets and more accurate and efficient IoT/IIoT-specific AIDS to be developed. Contribution to filling this research gap is the main target of our recent research work. In particular, our focus is on the generation of new labelled IoT/IIoT datasets that will be publicly available to the research community and include: (a) events reflecting multiple benign and attack scenarios from current IoT/IIoT network environments, (b) sensor measurement data, (c) network-related information (e.g., packet-level information and flow-level information) from the IoT/IIoT network, and (d) information related to the behaviour of the IoT/IIoT devices deployed within the IoT/IIoT network. It is worthwhile to mention that the new labelled IoT/IIoT datasets are generated by implementing various benign IoT/IIoT network scenarios and IoT/IIoT network attack scenarios in the Cooja simulator which is the companion network simulator of the open source Contiki OperatingSystem (OS) that is one of the most popular OSs for resource constrained IoT devices [14]. To the best of our knowledge, this is the first time that the Cooja simulator is going to be used, in a systematic way, to generate comprehensive IoT/IIoT datasets. In this paper, we present the approach that we followed to generate an initial set of benign IoT/IIoT datasets (i.e., including only normal events) and malicious IoT/IIoT datasets (i.e., including attack and normal events) by utilising the Cooja simulator that was the simulation environment where the corresponding benign and attack scenarios were implemented. The rest of this paper is organised as follows. In Section 2, the main threats against the IoT/IIoT network (i.e., perception domain) are presented and in Section 3, examples of anomaly-based intrusion detection systems for IoT/IIoT networks are discussed. In Section 4, a detailed description of the approach followed to generate a set of benign datasets by implementing a benign IIoT network scenario in the Cooja simulator is provided. In Section 5, a detailed description of the approach followed to generate a set of malicious datasets by implementing a User Datagram Protocol (UDP) flooding attack scenario in the Cooja is provided as well. In Section 6, a discussion on the generated datasets is given. Finally, Section 7 concludes this paper.