Innovations and Applications in Privacy-Preserving Tech in the Age of Data Privacy

PS101: Introduction to Privacy-preserving Secure Data Computation & Analytics (TGS-2020504778)


Course Overview

In today's digitized world, as per the government regulations like PDPA and GDPR, data privacy is an important concern for both private and public organizations. On the one hand, companies would like to use data to improve their products, on the other hand, individuals as customers would want to protect our privacy. This kind of contradicting needs is exactly where the privacy-preserving technologies can be applied to meet. The innovations in privacy-preserving technologies ensure that different kinds of statistical analyses don’t compromise data privacy. They allow organizations and businesses to collect information about their uses without compromising the personal privacy.

This course aims to introduce participants with the basic approaches in privacy-preserving technologies and their applications in machine learning, healthcare, government data etc. Approaches like secure multiparty computation, homomorphic encryption, synthetic data, and differential privacy offer capabilities for managing input, analytical, and output privacy and promote data accessibility and use. 


Course Duration

2 days

Course Mode

Synchronous e-learning

Course Intake

June 2021


Course Details

  • Introduction to Privacy-preserving Technologies: Background, Technology, and Use Cases
  • Technology Innovations: Homomorphic Encryption, Secure Multiparty Computation, Searchable Encryption, Differential Privacy
  • Privacy-preserving Technologies for Machine Learning
  • Privacy-preserving Technologies and PDPA
  • Business Applications

Note: NTC reserves the right to reserves the right to make changes to the above programme schedule according to the circumstances at any particular time.


Course Highlights

Explore solutions and plans for privacy-preserving technologies (PP-Tech). Main aims at providing solutions to related industry, adding value to the digital economy, and promoting social adoption.

Homomorphic Encryption schemes allow computations on ciphertext, without revealing information on plaintext. We design new fully homomorphic encryption (FHE) constructions based on new mathematical tools to efficiently secure data management on the cloud. To improve the efficiency of existing FHE constructions, we develop efficient computation algorithms on encrypted data.

Multi-Party Computation (MPC) schemes enables multiple parties to collaboratively perform computation without disclosing any party's private input. We design and implement secure MPC based on FHE, speed up the MPC of particular functions in terms of rounds, improve communication and computation complexities.

Symmetrical Searchable Encryption (SSE) schemes allow ciphertext searching which enables data to be securely stored at the cloud. Our work focuses on building flexible SSE schemes for ease of configuration in the level of security, search time, storage for application in practical large databases. We design leakage-resilient provable secure frameworks to maximize query capacity and improve existing structured encryption schemes to achieve performance-balanced expressive SSE.

Differential Privacy mechanism can be used to satisfy data aggregation without leaking individual private information. These algorithms rely on incorporating random noise into the data.

Course Instructors

- Introduction to Privacy-preserving Techniques: Background, Technology & Use Cases
- Technology Focus 2 - Secure Multi-Party Computation

Dr. Ijuawinata received his Ph.D. from the Department of Mathematical Sciences, the Nanyang Technological University Singapore.

Dr. Ijuawinata completed his B.Sc. degree with concentrations in Mathematical Sciences from the same university. Dr. Tjuawinata research focusing on the area of cryptanalysis, especially on symmetric key cryptosystem. At School of Physical and Mathematical Sciences, Division of Mathematical Sciences he received Teaching Assistant Award in 2018. He contributed in the development of a survey slides for Multiparty Computation Scheme.
His current research direction includes design of multiparty computation schemes and their application in machine learning and distributed cryptosystem.
Topic: Technology Focus 1 - Homomorphic Encryption

Dr. Xianhui Lu received his Ph.D. in information security from Southwest Jiaotong University in 2009.

Dr. Xianhu Lu is a research fellow in SCRiPTS of NTU an expert in Privacy protection of neural networks based on homomorphic encryption. Design homomorphic encryption schemes to support practical multiplications of fixed-point decimal vectors and non-linear functions such as sigmoid, ReLU and square. Explore efficient noise management algorithm to support homomorphic computation of large size numbers and large depth circuits without bootstrapping. Explore efficient message encoding algorithm to bridge the gap between the native data type of homomorphic encryption scheme and the target data type of applications.

He current research focuses on homomorphic encryption and post-quantum cryptography. He is one of the editors of the post-quantum study project of ISO/IEC SC27 WG2. He is the principal author of the algorithm LAC, which is currently one of the 26 second round candidates of the NIST Post-Quantum Cryptography Competition.

Topic: Technology Focus 3 - Searchable Encryption

Dr. Thong T. Nguyen received his Ph.D. from the School of Computer Science and Engineering, NTU. He completed his B.Sc degree in Computer Science from Ho Chi Minh City University of Technology.

Dr. Tong T. Nguyen research is at the intersection between differential privacy and machine learning. He contributed to the development of differentially private techniques for survival analysis models. He also proposed techniques to collect distributed data with local differential privacy.

His current research is on the applications of cryptographic techniques in training machine learning models with differential privacy guarantees.

Topic: Technology Focus 3 - Searchable Encryption

Dr. Melody research topic is local differential privacy technology (LDP). As LDP perturbs the users’ data locally before it leaves their own devices, nobody can access the original data except the data owner. It prevents single-point failures for data breaches and provides much stronger privacy protection. Therefore, it received a significant amount of attention and has been deployed by many big companies, such as Google, Apple, and Microsoft.

Her research mainly focusses on designing local differential privacy algorithm to support the statistics over the smaller population, and quantify the sample complexity. Currently, the main directions we considered are definition relaxation, privacy amplification and combination with MPC.

Topic: Technology Focus 4 - Differential Privacy and its Application

Dr. Zhao received his Ph.D. degree from the Department of Information Engineering, the Chinese University of Hong Kong.

Dr. Zhao under the supervision of Prof. Sherman S. M. Chow for his Ph.D. Before joining NTU, Dr. Zhao was a research fellow at the Chinese University of Hong Kong. He has been working on cryptographic cloud storage systems as well as private set-intersection protocols, resulting in publications in top-tier journals and conferences, e.g., IEEE Transactions on Dependable and Secure Computing (IEEE-TDSC), the International Conference on Practice and Theory in Public Key Cryptography (PKC), the annual Privacy Enhancing Technologies Symposium (PETS).

Dr. Zhao is interested in applying cryptography to privacy-enhancing technologies. He is now mainly working on symmetric searchable encryption in the Strategic Centre for Research in Privacy-Preserving Technologies & Systems, Nanyang Technological University.

Admission Info

Who Should Attend?

Engineers, Administrators in Information Security, IT& Network Infrastructure and System, Risk & Compliance, Automation & Process Control,  Data Analytic/Data Science Professionals, Entrepreneurs, and C-Suites are encouraged to attend this course.

Full Course Fees

S$1,988* per pax
*as low as S$ 240.55 after maximum SkillsFuture funding

1. SkillsFuture Series

Full Course Fees

Funding Type Subsidy Criteria 2-Day Course Fee
Base Grant 70%
(Capped at $13,000)
Singaporean / Singaporean PR Age 21 & Above Course Fee: $1988 - $1391.60 = $596.40
GST: $41.75
Full Fee Payable: $638.15
Mid Career
Enhanced Subsidy
(Capped at $13,000)
Singaporean Age 40 & Above Course Fee: $1988 - $1789.20 = $198.80
GST: $41.75
Full Fee Payable: $240.55
Enhanced Training Support
(Capped at $13,000)
Singaporean / Singaporean PR who is SME Sponsored  Course Fee: $1988 - $1789.20 = $198.80
GST: $41.75
Full Fee Payable: $240.55
SkillsConnect Course code for Privacy-preserving Technologies Programme: CRS-N-0051816

SkillsFuture Credit

Singapore Citizens aged 25 and above may use their SkillsFuture Credits (up to S$500) to pay for the course fees. The credits may be used on top of existing course fee funding. This is only applicable to self-sponsored participants. Applications via must be made within 60 days before course commencement. Please click here for the user guide on how to submit your claim.

From 1 April 2020, a one-off SkillsFuture Credit top-up of $500 will be provided to every Singapore Citizens aged 25 years and above as at 31 December 2020. This top-up will expire on 31 December 2025. Eligible Singaporeans can now start using their one-off credit top-up to offset the full fee payable.

3. Absentee Payroll

Companies who sponsor their employees for the course may apply for Absentee Payroll via the SkillsConnect system. For more information, please visit SkillsConnect. 

4. NTU Alumni Course Credit

From 1 July 2019, NTU alumni may utilise their course credits of S$1,600.00 to co-pay up to 50% of the nett fee (exclusive of prevailing GST) payable for courses with starting date from 1 July 2019 onwards. There will be no administrative fee involved for the use of NTU Alumni Course Credits on courses with starting date from 1 July 2019 onwards. For more information, please visit here

An online assessment will be conducted at the end of the course.


Registration is open till 7 June 2021. Click here to register.


For enquiries, contact us at

Mr Ambrose Chia

Registration is open.

12 Apr to 7 Jun 2021

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Ms Lim Bei Yi


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