Omkar2118/datasets huggingface dataset:
2devs

**2devs** is a publicly available dataset of fine-grained untangled code changes collected by recording the development sessions of two developers over the course of four months, and the corresponding manual clustering.

Introducing paper: Untangling Fine-Grained Code Changes
ToN_IoT

The **TON_IoT** datasets are new generations of Internet of Things (IoT) and Industrial IoT (IIoT) datasets for evaluating the fidelity and efficiency of different cybersecurity applications based on Artificial Intelligence (AI). The datasets have been called ‘ToN_IoT’ as they include heterogeneous data sources collected from Telemetry datasets of IoT and IIoT sensors, Operating systems datasets of Windows 7 and 10 as well as Ubuntu 14 and 18 TLS and Network traffic datasets. The datasets were collected from a realistic and large-scale network designed at the IoT Lab of the UNSW Canberra Cyber, the School of Engineering and Information technology (SEIT), UNSW Canberra @ the Australian Defence Force Academy (ADFA). 

The datasets were gathered in a parallel processing to collect several normal and cyber-attack events from IoT networks. A new testbed was developed at the IoT lab to connect many virtual machine, physical systems, hacking platforms, cloud and fog platforms, IoT and IIoT sensors to mimic the complexity and scalability of industrial IoT and Industry 4.0 networks.

Different hacking techniques, such as DoS, DDoS and ransomware against, were launched against web applications, IoT gateways and computer systems across the IIoT network.

Introducing paper: Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications