6 citations · 25 across the 15 of their papers we have counts for
15 papers
Scalable AI-Driven Analytics for User Engagement and Stance Detection on Social Media
Thammitage Piyumi Wathsala Seneviratne, Muhammad Ikram, Dinusha Vatsalan +2
Social media platforms have become a major vector for the large-scale dissemination of misinformation and conspiracy content, posing significant risks to public trust, health, and…
Protecting User Prompts Via Character-Level Differential Privacy
Shashie Dilhara Batan Arachchige, Hassan Jameel Asghar, Benjamin Zi Hao Zhao +2
Large Language Models (LLMs) generate responses based on user prompts. Often, these prompts may contain highly sensitive information, including personally identifiable information…
CTIGuardian: A Few-Shot Framework for Mitigating Privacy Leakage in Fine-Tuned LLMs
Shashie Dilhara Batan Arachchige, Benjamin Zi Hao Zhao, Hassan Jameel Asghar +2
Large Language Models (LLMs) are often fine-tuned to adapt their general-purpose knowledge to specific tasks and domains such as cyber threat intelligence (CTI). Fine-tuning is mos…
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…
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 (…
Privacy-Preserving Record Linkage for Cardinality Counting
Nan Wu, Dinusha Vatsalan, Mohamed Ali Kaafar +1
Several applications require counting the number of distinct items in the data, which is known as the cardinality counting problem. Example applications include health applications…
Privacy-Preserving Record Linkage
Dinusha Vatsalan, Dimitrios Karapiperis, Vassilios S. Verykios
Given several databases containing person-specific data held by different organizations, Privacy-Preserving Record Linkage (PPRL) aims to identify and link records that correspond…
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…
Local Differentially Private Fuzzy Counting in Stream Data using Probabilistic Data Structure
Dinusha Vatsalan, Raghav Bhaskar, Mohamed Ali Kaafar
Privacy-preserving estimation of counts of items in streaming data finds applications in several real-world scenarios including word auto-correction and traffic management applicat…
Fairness and Cost Constrained Privacy-Aware Record Linkage
Nan Wu, Dinusha Vatsalan, Sunny Verma +1
Record linkage algorithms match and link records from different databases that refer to the same real-world entity based on direct and/or quasi-identifiers, such as name, address,…
Privacy Preserving Release of Mobile Sensor Data
Rahat Masood, Wing Yan Cheng, Dinusha Vatsalan +3
Sensors embedded in mobile smart devices can monitor users' activity with high accuracy to provide a variety of services to end-users ranging from precise geolocation, health monit…
Data and Model Dependencies of Membership Inference Attack
Shakila Mahjabin Tonni, Dinusha Vatsalan, Farhad Farokhi +3
Machine learning (ML) models have been shown to be vulnerable to Membership Inference Attacks (MIA), which infer the membership of a given data point in the target dataset by obser…
Incremental Clustering Techniques for Multi-Party Privacy-Preserving Record Linkage
Dinusha Vatsalan, Peter Christen, Erhard Rahm
Privacy-Preserving Record Linkage (PPRL) supports the integration of sensitive information from multiple datasets, in particular the privacy-preserving matching of records referrin…
Scalable Multi-Database Privacy-Preserving Record Linkage using Counting Bloom Filters
Dinusha Vatsalan, Peter Christen, Erhard Rahm
Privacy-preserving record linkage (PPRL) aims at integrating sensitive information from multiple disparate databases of different organizations. PPRL approaches are increasingly re…
Multi-Party Privacy-Preserving Record Linkage using Bloom Filters
Dinusha Vatsalan, Peter Christen
Privacy-preserving record linkage (PPRL), the problem of identifying records that correspond to the same real-world entity across several data sources held by different parties wit…