In June 2017, a seed grant call was launched to invite proposals from consortium members for proof-of-concepts of new cybersecurity technologies and innovative ideas. Six projects were awarded based on their technical merits and potential for commercialisation.
Details of Awarded Projects
An Integrated Safety-Security Approach for Engineering Unmanned Aerial Systems (UAS) Traffic Management Solutions
This project aims to develop an integrated safety-security approach for Unmanned Aerial Systems (UAS) traffic management (UTM) systems, through a safety-security co-analysis and risk assessment framework. It will establish best-practice and safety-and-security-by-design guidelines for this approach.
This project is a collaboration between Advanced Digital Sciences Center, a Singapore-based research centre that is an affiliate of the University of Illinois at Urbana-Champaign, Singapore-based company Nova Systems & Engineering, Canada’s Critical System Labs Inc, University of Illinois at Urbana-Champaign, and Singapore-based company NSHC Pte Ltd.
Identification of IoT Devices behind NAT while Ensuring the Preservation of Data Privacy
This project aims to develop a method to passively map out Internet of Things (IoT) devices in users’ premises while preserving privacy. This will help build a security layer between IoT devices and telecommunications infrastructure to monitor and detect potentially malicious traffic.
Learning to Detect Anomalies in Cyber-Physical Systems with Generative Adversarial Networks on Networked Sensor Time Series Data
This project aims to develop a machine learning approach using generative adversarial networks. It will simultaneously train a deep learning network to model normal behaviour in a cyber-physical system, while also detect anomalies due to cyber attacks in the networked sensor time series. It will be evaluated using a realistic complex cyber-physical system dataset from the Secure Water Treatment Testbed.
Mobile (iOS) Security Study for Cyber-Attack Prevention
This project aims to build an assessment framework for iOS malware, which is less studied than Android malware. The framework aggregates iOS malware into a database and performs a suite of analysis and classification techniques to derive a risk score, and hence recommend actions to fix or mitigate the malware impact.
No More Snake Oil - Objective Evaluation Environment for Security Technologies
This project aims to develop a proof-of-concept testing environment for security technologies, which could also serve as a demonstration platform for solution developers. It will include simulation of various network-based attack scenarios and techniques, and an automatic scoring or measurement framework. It will be validated through applications on Singapore-based start-up InsiderSecurity’s technologies.
Secure Dataset Sharing for Remote Artificial Intelligence Innovations on Clinical Data
This project aims to develop a platform for secure sharing and consumption of research data, with automatic data sensitisation, centralised access control, cryptographic key exchange, and a client application to execute user codes on the data. It will be built on Singapore-based start-up Cloak’s existing platform and tested with clinical data from the Agency for Science, Technology and Research (A*STAR) Bioinformatics Institute’s partner hospitals.