Overview of thesis
Identification of intrusion patterns on selected network traffic to develop an accurate and efficient detection approach
With organisations heavily relying on cyber-enabled infrastructures, cybercrime and cyber-attacks are subsequently increasing. Existing cyber-security strategies need to be both accurate and efficient in order to process current and predicted network traffic flows. Improving current cyber-security strategies is essential.
The purpose of the research project is to develop a hybrid detection approach that accurately identifies cyber-attacks against assets on the cyber-enabled infrastructure, while also efficiently processing current and predicted network traffic flows. The study aims to develop a hybrid data mining intrusion detection approach that uses decision tree classifications and association rule mining to extract rules. This will result in a set of procedural probability rules that can be deployed by an Intrusion Detection System (IDS).
- BScHons (Bachelor of Computer Science Honours), Edith Cowan University, July 2013-July 2014.
- BSc (Bachelor of Computer Science), Edith Cowan University, Jan 2010- July 2013.
- Network security (detection and analysis)
- Data analysis
- Pattern identification
Recent Publications (within the last five years)
Conference Publications/ Presentations
- Valli, C., Rabadia, P., Woodward, A., (2015), A Profile of Prolonged, Persistent SSH Attack on a Kippo Based Honeynet. Proceedings of the 10th Annual ADFSL Conference on Digital Forensics, Security and Law, 23-32.
- Rabadia, P., Valli, C., (2015), Analysis into developing accurate and efficient intrusion detection approaches. Proceedings of 13th Australian Digital Forensics Conference, 70-76, Perth, WA.
- Rabadia, P., Valli, C., (2014), Finding evidence of wordlists being deployed against SSH Honeypots - implications and impacts. Proceedings of 12th Australian Digital Forensics Conference, 114-121, Perth, W.A.
- Valli, C., Rabadia, P., Woodward, A., (2013), Patterns and Patter - An Investigation Into SSH Activity Using Kippo Honeypots. The Proceedings of 11th Australian Digital Forensics Conference, 141-149, Edith Cowan University.
ECU Security Research Institute
School of Science