About SCRIPTS
What We Do
SCRIPTS specialises in privacy-preserving technologies (PP-Tech) that are computing techniques used to preserve individual’s privacy while allowing maximum value and insight to be extracted from available data. These technologies enable organisations to carry out data mining, analysis and sharing in compliance with data protection regulation enacted in various jurisdictions. PP-Tech will provide solutions and knowledge on how to best utilise data collected to benefit Singapore’s advancement towards a Smart Nation without compromising privacy.
The Centre focuses on the research, development and application of customised privacy-preserving technologies aligned with the national priorities of Singapore in the Services and Digital Economy of the Research, Innovation, and Enterprise (RIE) 2020 plan. Our work is funded by a $15.3 million grant from the Infocomm Media Development Authority (IMDA), and supported by the National Research Foundation, Singapore (NRF).
Research Focus
Learn moreWe explore the following PP-Tech with the aim of providing solutions to government and industry, adding value to the digital economy, and promoting social adoption.
Student Testimonial
I enrolled at NTU in 2022 to pursue a M.Eng degree under the supervision of Prof. Lam Kwok Yan. I am thrilled to share that I have recently graduated and started my next journey as a data scientist at a German company. I am deeply grateful for Prof. Lam’s unwavering support and thoughtful guidance. His mentorship provided me with an excellent opportunity to explore advanced topics, complemented by his invaluable insights, extensive knowledge, and vast experience. Under his supervision, I had the privilege of working in a conducive environment with ample time to delve into meaningful and impactful research. The dedication and rigorous approach to research that Prof. Lam instilled in me will remain a lifelong treasure and a cornerstone of my future career journey.
Shen Jiyuan, SCRIPTS Scholarship Recipient in AY2022/2023
Events
View all eventsSeminar by Prof Yi Xun, RMIT University, Australia, 28 Nov 2024, RTP Harvard Room
Time: 28 Nov 2024, 2pm to 3pm
Venue: Research Techno Plaza (RTP), Level 2, Harvard Room
Title: Contact Tracing with Location Privacy Protection
Bio: Dr. Xun Yi is a full professor at RMIT University, Melbourne, Australia. He obtained his PhD from Xidian University, China in 1995. His research interests include data privacy and security, network security, and applied cryptography. He has published more than 250 journal and conference papers, attracting more than 8,000 citations. He has successfully led 11 Australian Research Council (ARC) projects, a Data61-RMIT CRP project, and participated in a collaborative project with Nanyang Technological University (NTU) funded by the Singapore government. From 2017 to 2019, Professor CI Yi served on various selection panels for the ARC, including the Discovery Project Selection Panel, Linkage Project Selection Panel, and DECRA Project Selection Panel. CI Yi has supervised more than 20 PhD students and 8 postdoctoral research fellows.
Abstract: The impact of COVID-19 has shown the need of contact tracing to quickly discover new infections and flatten the infection curve. Contact tracing deals with the challenge of identifying people who have had close contacts with individuals confirmed to be infected, which also helps identifying unreported infected people. When designing contact tracing systems, privacy protection of the citizens and power consumption of mobile devices are key considerations in order to minimise hurdles and enhance people's trust in adopting the systems. In this talk, we present three contact tracing protocols (basic, improved, advanced) based on homomorphic encryption, where multiple servers collaborate to perform contact tracing. The basic and improved protocols can protect location privacy for contactless mobile users, while the advanced protocol can protect both location and quarantine privacy for any mobile users, as long as one of multiple servers is honest.
Patents
Lam Kwok Yan, et. al. Privacy-Preserving Neural Network Based on FHE Scheme, Fast Track Provisional Filing, 24 February 2022. Singapore provisional patent application number 10202201824W.
Lam Kwok Yan, et. al. Optimization Of FHE Scheme For Non-Linear Functions: An Efficient Design For LUT-Based Non-Linear Function Evaluation, Fast Track Provisional Filing, 13 May 2022. Singapore provisional patent application number 10202205037W.
Lam Kwok Yan, et. al. Privacy-Preserving Neural Network Model And Privacy-Preserving Prediction Using The Privacy-Preserving Neural Network Model, PCT Patent International Filing (claiming priority to earlier SG application nos. 10202201824W & 10202205037W), 15 February 2023, PCT Application No: PCT/SG2023/050085. International Publication No: WO 2023/163652 A2, 31 August 2023.
Lam Kwok Yan, et. al. Efficient FHE-Based Training On Encrypted Data, 23 January 2024, Singapore provisional patent application number 10202400198U.
Lam Kwok Yan, et. al. Two-Party Privacy-Preserving Subgraph Checking Over Unlabeled Graphs, 15 April 2024, Singapore provisional patent application number 10202401083W.