Researchers at UNSW have raised $1.3 million to fund a spin-out business using software they developed to protect internet of things (IoT) devices from cyber attacks.
The company, known as CyAmast, was formed in May this year to commercialise software and research developed by Dr Hassan Habibi at UNSW’s School of Electrical Engineering and Telecommunications.
The software allows users to identify, detect and classify all IoT devices on their network, and to profile and model their behaviour.
By continually monitoring network traffic, CyAmast’s solution is able to intelligently detect deviations in the intended patterns of device behaviour.
This is said to be a more flexible, cost-effective and scalable solution than current approaches that spot attacks on IoT networks by inspecting individual data packets to determine threat signatures, Habibi said.
“Traditional methods of detecting malicious traffic are bundled, static, and inflexible, and thus do not suffice for the growing diversity of attacks on increasing numbers of insecure IoT devices,” he said.
“These attack-signature-based solutions are increasingly being defeated as they can’t keep up with the increasing percentage of network traffic that’s encrypted and therefore can’t be opened and inspected.
“They also have poor resilience to morphed attacks that can render known signatures useless.”
Inspecting individual packets can also be prohibitively expensive, he added.
The new funding for the spin-off comes from research commercialisation firm IP Group.
Michael Molinari, IP Group’s Australian managing director, said the CyAmast’s solution has ready applications in industry.
“The use of IoT devices and sensors is growing exponentially, and as organisations’ networks expand, it’s increasingly difficult to track these assets and secure them,” he said.
“Dr Habibi and his team have developed technology that enables operators of smart environments - like enterprise campuses, commercial buildings, industrial facilities and airports - to rapidly identify every IoT device connected to their network and continuously monitor each one and ensure that it’s functioning normally.”
On top of scalability, the software can process large volumes of data quickly, Habibi added.
“This all happens at 100s of Gbps (billions of bits per second) without the dependence of highly customised and expensive infrastructure.”
Habibi and his team were previously awarded a research grant from Google to model and enforce cyber security for large-scale IoT networks.
