We were engaged by researchers at Edith Cowan University, as part of the Cyber Security CRC program, to systemise the gathering of in-depth research to be used to better train users to handle cyber security risks and threats.
Ideally, the researchers were wanting data gathering via a simulated 'Cybersecurity Intrusion Detection System'. This intrusion system was to operate similarly to commercial intrusion detection software but with the additional functionality of capturing and analysing user behaviour.
The key deliverable was to ensure the software could analyse the performance of users in real time and determine their vigilance level.
We developed a cross-platform desktop application which utilised a reactive programming model to drive the simulated network intrusion events and data capture. We initially prototyped this model in a matter of hours and were quick to get this back in the hands of researchers to gather feedback on utility as quickly as possible.
The core technologies utilised were Electron, TypeScript, and RxJS.
Our application allows researchers to configure custom trial parameters to change the simulation difficulty over time. Once users of the system proceed through the threat simulator, researchers are provided with an export of raw data and also processed behavioural data.
- Simulate threat analysis via an Intrusion Detection System.
- Providing researchers with deep insights to better improve cyber security protocols.
- Track performance of user behaviour with real time data.
Backend Development, Cloud Architecture, Machine Learning.