Datasets as described in the research paper "Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT Applications".There are two main dataset provided here, firstly is the data relating to the initial training of the machine learning module for both normal and malicious traffic, these are in binary visulisation format, compresed into the document


Each dataset is provided in compressed ZIP files, no password protection is present and no malicious files are contained herein, only their network traffic and image representations relevant to the project.


The rise of the Internet of Things (IoT) has opened new research lines that focus on applying IoT applications to domains further beyond basic user-grade applications, such as Industry or Healthcare. These domains demand a very high Quality of Service (QoS), mainly a very short response time. In order to meet these demands, some works are evaluating how to modularize and deploy IoT applications in different nodes of the infrastructure (edge, fog, cloud), as well as how to place the network controllers, since these decisions affect the response time of the application.