The application of epidemiology to cyber security

Scholarships of $35K AUD for domestic and international students are available for Masters and PhD by research.

Background

With the spread of IoT devices, security issues are becoming more severe, in part because of the large scale and heterogeneous nature of the devices.

There are an increasing number of insecure IoT devices with a high computational power, this makes them attractive targets for botnet creators. Compromised IoT devices can be aggregated together through command and control servers to perform a diverse set of activities including; distributed denial of service, password cracking, and crypto-currency mining.

Techniques in epidemiology that are pertinent to malware detection include threat detection, source analysis, risk analysis, and spread estimation.

These techniques could be used to firstly detect spread, and predict spread of both known and unknown malware. These techniques could be used to determine risk of infection and perform ameliorative actions.

Research aims

A novel process for the detection of and tracking of botnets.

A novel process for the detection of malware activity on a local network.

Contact:

Contact Dr Tim Lynar t.lynar@adfa.edu.au for further information.

Supervisor