Security

Unmanned aerial vehicles (UAVs) are being used for various applications, but the associated cyber risks are also increasing. Machine learning techniques have been successfully adopted to develop intrusion detection systems (IDSs). However, none of the existing works published the cyber or physical datasets that have been used to develop the IDS, which hinders further research in this field.

The high profitability of mining cryptocurrencies mining, a computationally intensive activity, forms a fertile ecosystem that is enticing not only legitimate investors but also cyber attackers who invest their illicit computational resources in this area. Cryptojacking refers to the surreptitious exploitation of a victim’s computing resources to mine cryptocurrencies on behalf of the cybercriminal. This malicious behavior is observed in executable files and browser executable codes, including JavaScript and Assembly modules, downloaded from websites to victims’ machines and executed.

The dataset used in the study consists of different IoT network traffic data files each IoT traffic data has files containing benign, i.e. normal network traffic data, and malicious traffic data related to the most common IoT botnet attacks which are known as the Mirai botnet.

each application has up to two files. One for memory dataset and another for control flow dataset. Each dataset is composed of JSON objects. Each instruction is a JSON object.