52 citations · 69 across the 15 of their papers we have counts for
17 papers
Curvature-Aware Clipping: Mitigating Bias in DPSGD via Approximate Second-Order Information
Xincheng Xu, Thilina Ranbaduge, Thierry Rakotoarivelo +1
Differentially Private Stochastic Gradient Descent (DPSGD) has become the de facto standard for training deep neural networks with rigorous privacy guarantees. However, the utility…
Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering
Xincheng Xu, Thilina Ranbaduge, Qing Wang +2
Differentially Private Stochastic Gradient Descent (DPSGD) is widely used to train deep neural networks with formal privacy guarantees. However, the addition of differential privac…
Embedding based Encoding Scheme for Privacy Preserving Record Linkage
Sirintra Vaiwsri, Thilina Ranbaduge
To discover new insights from data, there is a growing need to share information that is often held by different organisations. One key task in data integration is the calculation…
From Detection to Correction: Backdoor-Resilient Face Recognition via Vision-Language Trigger Detection and Noise-Based Neutralization
Farah Wahida, M. A. P. Chamikara, Yashothara Shanmugarasa +3
Biometric systems, such as face recognition systems powered by deep neural networks (DNNs), rely on large and highly sensitive datasets. Backdoor attacks can subvert these systems…
From 5G to 6G: A Survey on Security, Privacy, and Standardization Pathways
Mengmeng Yang, Youyang Qu, Thilina Ranbaduge +12
The vision for 6G aims to enhance network capabilities with faster data rates, near-zero latency, and higher capacity, supporting more connected devices and seamless experiences wi…
Integrating PETs into Software Applications: A Game-Based Learning Approach
Maisha Boteju, Thilina Ranbaduge, Dinusha Vatsalan +1
The absence of data protection measures in software applications leads to data breaches, threatening end-user privacy and causing instabilities in organisations that developed thos…
Privacy Technologies for Financial Intelligence
Yang Li, Thilina Ranbaduge, Kee Siong Ng
Financial crimes like money laundering and terrorism financing can have significant impacts on society, including loss of trust in the integrity of the financial system, misuse and…
Private Knowledge Sharing in Distributed Learning: A Survey
Yasas Supeksala, Dinh C. Nguyen, Ming Ding +5
The rise of Artificial Intelligence (AI) has revolutionized numerous industries and transformed the way society operates. Its widespread use has led to the distribution of AI and i…
Privacy risk in GeoData: A survey
Mahrokh Abdollahi Lorestani, Thilina Ranbaduge, Thierry Rakotoarivelo
With the ubiquitous use of location-based services, large-scale individual-level location data has been widely collected through location-awareness devices. The widespread exposure…
SoK: Demystifying Privacy Enhancing Technologies Through the Lens of Software Developers
Maisha Boteju, Thilina Ranbaduge, Dinusha Vatsalan +1
In the absence of data protection measures, software applications lead to privacy breaches, posing threats to end-users and software organisations. Privacy Enhancing Technologies (…
Differentially Private Vertical Federated Learning
Thilina Ranbaduge, Ming Ding
A successful machine learning (ML) algorithm often relies on a large amount of high-quality data to train well-performed models. Supervised learning approaches, such as deep learni…
Privacy-preserving Deep Learning based Record Linkage
Thilina Ranbaduge, Dinusha Vatsalan, Ming Ding
Deep learning-based linkage of records across different databases is becoming increasingly useful in data integration and mining applications to discover new insights from multiple…
Vertical Federated Learning: Challenges, Methodologies and Experiments
Kang Wei, Jun Li, Chuan Ma +5
Recently, federated learning (FL) has emerged as a promising distributed machine learning (ML) technology, owing to the advancing computational and sensing capacities of end-user d…
Private Graph Data Release: A Survey
Yang Li, Michael Purcell, Thierry Rakotoarivelo +3
The application of graph analytics to various domains has yielded tremendous societal and economical benefits in recent years. However, the increasingly widespread adoption of grap…
Large Scale Record Linkage in the Presence of Missing Data
Thilina Ranbaduge, Peter Christen, Rainer Schnell
Record linkage is aimed at the accurate and efficient identification of records that represent the same entity within or across disparate databases. It is a fundamental task in dat…
Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching
Sirintra Vaiwsri, Thilina Ranbaduge, Peter Christen +1
The task of calculating similarities between strings held by different organizations without revealing these strings is an increasingly important problem in areas such as health in…
Temporal graph-based clustering for historical record linkage
Charini Nanayakkara, Peter Christen, Thilina Ranbaduge
Research in the social sciences is increasingly based on large and complex data collections, where individual data sets from different domains are linked and integrated to allow ad…