31 citations · 34 across the 5 of their papers we have counts for
5 papers
SKALD: Scalable K-Anonymisation for Large Datasets
Kailash Reddy, Novoneel Chakraborty, Amogh Dharmavaram +1
Data privacy and anonymisation are critical concerns in today's data-driven society, particularly when handling personal and sensitive user data. Regulatory frameworks worldwide re…
Privacy-Preserving Data Quality Assessment for Time-Series IoT Sensors
Novoneel Chakraborty, Abhay Sharma, Jyotirmoy Dutta +1
Data from Internet of Things (IoT) sensors has emerged as a key contributor to decision-making processes in various domains. However, the quality of the data is crucial to the effe…
Building a Privacy Web with SPIDEr -- Secure Pipeline for Information De-Identification with End-to-End Encryption
Novoneel Chakraborty, Anshoo Tandon, Kailash Reddy +5
Data de-identification makes it possible to glean insights from data while preserving user privacy. The use of Trusted Execution Environments (TEEs) allow for the execution of de-i…
Mean Estimation with User-Level Privacy for Spatio-Temporal IoT Datasets
V. Arvind Rameshwar, Anshoo Tandon, Prajjwal Gupta +3
This paper considers the problem of the private release of sample means of speed values from traffic datasets. Our key contribution is the development of user-level differentially…
Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems
Amy LaViers, Catie Cuan, Madison Heimerdinger +10
As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a h…