Predictive Security Analytics

Research activities under this theme will involve developing technologies that automate and update organisations’ predictive capabilities for early detection of potential network and software threats through analysis of a variety of data streams.

NUS will contribute expertise in machine learning, software security, human behaviour modelling and network domain knowledge to create advanced techniques and tools to enable IT systems to detect security threats and other abnormal activities, such as malicious software intrusion or leakage of data, more accurately and in real time.

With predictive security analytics, Singtel Managed Security Services can receive timely intelligence, and allow its security professionals to quickly take pre-emptive action to thwart any impending cyber threats. Further, through the aid of analytics, enterprises and government agencies will have access to relevant data and information that will help in making more accurate decisions.

Principal Investigators

- Chan Mun Choon (Theme Leader)
- Dong Jin Song
- Liang Zhenkai
- Bryan Low Kian Hsiang
- Abhik Roychoudhury
- Roland Yap