Security

As our everyday lives become increasingly digital, it is crucial to ensure that our data

and privacy is secure.​

From blockchain security and cryptography to infrastructure security, we design, develop, and deploy solutions for improving security and privacy across both software and hardware computer systems.

What We Do

Construct and analyse protocols to prevent third parties (or adversaries) from maliciously accessing data.
Develop solutions to combat security breaches caused by hardware failure.
Study techniques to detect and prevent unauthorised access to computer and Internet network systems.
Explore issues and developments in biometrics, multimedia, and machine learning security.
Analyse threats across all areas of security, developing solutions to preserve privacy and develop secure computing systems.

Sub Areas

Our Research Projects

Analytical Framework to Quantify Information Leakage and Memorization in Machine Learning

Reza SHOKRI

Machine learning models can "memorize" specific data points from their training data, impacting their predictions and potentially leaking sensitive information. This project aims to understand how this memorization affects models and develop methods to mitigate it.


Fuzz Testing

Abhik ROYCHOUDHURY

  • TRL 4
  • Software Security & Analysis

BCube and Flint: Overcoming the 50% Barrier in Blockchains

YU Haifeng


Computational Hardness Assumptions and the Foundations of Cryptography

Prashant Nalini VASUDEVAN

This program seeks to broaden and diversify the foundations of cryptography by identifying new plausible computational hardness assumptions that can be used to construct cryptosystems. Our current approach is to study and construct "fine-grained" cryptographic primitives based on the conjectured hardness of various well-studied algorithmic problems.

  • Cryptography

SQLancer: Automatic Testing of Database Management Systems

Manuel RIGGER

SQLancer automatically finds logic bugs in Database Management Systems (DBMSs). We have used SQLancer to find and report over 500 unique, previously unknown bugs in widely-used DBMSs. In addition, SQLancer has been widely adopted in the industry.

  • TRL 9
  • Software Testing

From iteration on multiple collections in synchrony to fast general interval joins

WONG Lim Soon

Synchrony iterator captures a programming pattern for synchronized iterations. It is a conservative extension that enhances the repertoire of algorithms expressible in comprehension syntax. In particular, efficient general synchronized iterations, e.g. linear-time algorithms for low-selectivity database non-equijoins, become expressible naturally in comprehensinon syntax.

  • TRL 4

Foundational Research Capabilities (FRC) Study on Foundations of Security and Data Privacy

Abhik ROYCHOUDHURY

This study was undertaken on behalf of National Research Foundation (NRF) Singapore, to study long-term plans in Security and Privacy foundations, and for further growing foundational research capabilities in Singapore. The study team was led by Abhik Roychoudhury from NUS, and had team members from NUS, NTU, SMU, CSA, A*STAR. The team submitted its report and recommendations at the end of 2022.


National Cybersecurity R&D Laboratory

CHANG Ee Chien

  • Infrastructure Security & Experimentation

Automated Program Repair

Abhik ROYCHOUDHURY

  • TRL 4
  • Software Security & Analysis

Active Defense Mechanism against Adversarial Attacks

CHANG Ee Chien

  • Machine Learning & AI Security

Intelligent Modelling for Decision-Making in Critical Urban Systems - DesCartes

Abhik ROYCHOUDHURY


Trustworthy de-centralized (federated) learning

Reza SHOKRI


Robustness and security in machine learning

Reza SHOKRI


Auditing data privacy (in machine learning)

Reza SHOKRI


Our Research Groups

Verified Systems Engineering

Ilya SERGEY

We do research in the design and implementation of programming languages (PL), mathematical models of computation, and computer-assisted formal reasoning. We investigate the theoretical foundations of programming and build tools for ensuring that certain kinds of costly software errors and vulnerabilities never occur in the real-world code, which many people rely upon in their everyday lives.

  • Blockchain Security, Fintech Security, Trustworthy Computing

Data Privacy and Trustworthy Machine Learning Lab

Reza SHOKRI