A suite of cutting-edge cyber honeypot technology has been developed by Australian students, researchers and industry professionals. The DecaaS (Deception as a Service) Project uses machine learning (ML) models to create highly realistic albeit fake versions of digital assets that are attractive to hackers. The team remarked that the approach of using honey pots was developed to rapidly detect if people have broken into a system about the intent, equipment and processes that adversaries are using. The project’s lead researcher, Dr. Kristen Moore of Australia’s national science agency, CSIRO, explained that the DecaaS project team has created models to generate fake content and traffic, including code repositories, email servers, Wi-Fi traffic and Wiki corpora, to create a convincing cyber honeypot. Furthermore, officials at the Cyber Security Cooperative Research Center noted that these are real-world threats with potentially devastating consequences. The DecaaS project commenced in November 2019 alongside CSIRO’s industry partner. The project is supported by Cyber-Security CRC and aims to apply cutting-edge machine learning and artificial intelligence to generate realistic computer systems and assets to deceive intruders who make their way into a system. As cyber threats increase in volume and sophistication, AI and machine learning offer an opportunity to assist overwhelmed human defenders and speed up decision-making and response. This is in addition to delivering more agile defences in a way that was not previously possible.