The dataset is available in GitHub and the link is given below:

https://github.com/sahilarora3117/capstone-19BCE1366-2023

Future IPv6-based networks face a significant security challenge with ICMPv6 communications. An attacker uses ICMPV6 messages to saturate the target system and aims to implement a Denial of Service (DoS) or Distributed Denial of Service (DDoS) attack. A robust intrusion detection system is being developed by researchers to address these issues. Researchers have access to a restricted number of IPv6 datasets to construct a well-known intrusion detection system, however these datasets are not accessible to the public and only target on one kind of attack.

The deployment of unmanned aerial vehicles (UAV) for logistics and other civil purposes is consistently disrupting airspace security. Consequently, there is a scarcity of robust datasets for the development of real-time systems that can checkmate the incessant deployment of UAVs in carrying out criminal or terrorist activities. VisioDECT is a robust vision-based drone dataset for classifying, detecting, and countering unauthorized drone deployment using visual and electro-optical infra-red detection technologies.

In the digital era of the Industrial Internet of Things (IIoT), the conventional Critical Infrastructures (CIs) are transformed into smart environments with multiple benefits, such as pervasive control, self-monitoring and self-healing. However, this evolution is characterised by several cyberthreats due to the necessary presence of insecure technologies. DNP3 is an industrial communication protocol which is widely adopted in the CIs of the US. In particular, DNP3 allows the remote communication between Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA).