An Efficient Cyber Threat Detection Method based on a Novel Meta-heuristic Algorithm and an Enhanced Classification Algorithm for a Real-world Cyber Dataset

Project Member(s): Gandomi, A.

Funding or Partner Organisation: Digital Finance CRC Limited (Digital Finance CRC)
Digital Finance CRC Limited (Digital Finance CRC)

Start year: 2022

Summary: This research study proposes a novel meta-heuristic algorithm to make the suggested classification algorithm more efficient in detecting cyber threats. In other words, an application-specific intelligent meta-heuristic algorithm will be proposed to improve the classifier performance in a cost-effective and time-efficient manner. After detecting the threats, they should also be classified as potential risks the relevant company faces. Hence, another efficient classifier using an intelligent meta-heuristic or hyper-heuristic algorithm will be proposed to make a risk detection and assessment task. Finally, the effect of the suggested method on threat detection, risk detection, and risk assessment in a large-scale real-world cyber dataset will be investigated.

FOR Codes: Cybersecurity, Artificial intelligence, Expanding knowledge in the information and computing sciences, Machine learning, Cybersecurity and privacy, Cybercrime

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.