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Malware Detection using Deep Learning
As the malware landscape quickly evolves, the use of artificial intelligence (AI) is a probable way to keep up with it.However, this requires huge volume of data to train on
Paper accepted at the Conference
Many Congratulations to Chris Chew Jun Wen for his paper (ESCAPADE: Encryption-type-ransomware: System Call based Pattern Detection) got accepted at the 14th International Conference on Network and System Security. The link to the paper will be uploaded soon.
Postdoctoral Research Fellow position is open for Human-Centric Security project
The AI for Human-Centric Security is a Catalyst project funded by MBIE. The project aims to use AI to aid human security experts in managing configuration in a diverse environment.

A Bilinear Pairing Based Secure Data Aggregation Scheme for WSNs
A Wireless Sensor Network (WSN) is a network of small battery-powered motes also known as wireless sensors, which have sensing, processing and communication capabilities
Behaviour based ransomware detection
Ransomware is an ever-increasing threat in the world of cybersecurity targeting vulnerable users and companies
Progger
An Efficient, Tamper-Evident Kernel-Space Logger for Cloud Data Provenance Tracking

Ransomware System Call Dataset
We have two sets of Android APK dataset available, Malware and Benign.
Progger
Progger (Provenance Logger) is a kernel-space logger designed to track data activity in Cloud systems.