Authors: Gokularam M, Anshoo Tandon Know more Differentially private K-means clustering enables releasing cluster centers derived from a dataset while protecting the privacy of the individuals. Non-interactive clustering techniques based on privatized histograms are attractive because the released data synopsis can be reused for other downstream tasks without additional privacy loss. The choice of the […]

Authors: Bryan Paul Robert, Mahidhar Chellamani, Jyotirmoy Dutta Know more For years, some of India’s most valuable geospatial datasets remained scattered across government departments, research institutes, or private organizations. They held immense potential to transform logistics, strengthen climate resilience, and support smarter urban planning, but they remained difficult to access, buried in different formats and […]

Authors: M. Yashwanth, G. K. Nayak, A. Singh, Y. Simmhan, A. Chakraborty Know more Federated Learning (FL) is a machine learning paradigm that enables clients to jointly train a global model by aggregating the locally trained models without sharing any local training data. In practice, there can often be substantial heterogeneity (e.g., class imbalance) across […]

Authors: N. Chakraborty, A. Sharma, J. Dutta. H. D. Kumar Know more This paper proposes a novel framework for automated, objective, and privacy-preserving data quality assessment of time-series data from IoT sensors deployed in smart cities. We leverage custom, autonomously computable metrics that parameterise the temporal performance and adherence to a declarative schema document to […]

Authors: N. Chakraborty, A. Tandon, K. Reddy, K. Kirpekar, B. Robert, H. Kumar, A. Venkatesh, A. Sharma Know more 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-identification applications on the cloud without the need for a […]

Authors: V. A. Rameshwar, A. Tandon, and A. Sharma Know more This paper considers the epsilon-differentially private (DP) release of an approximate cumulative distribution function (CDF) of the samples in a dataset. We assume that the true (approximate) CDF is obtained after lumping the data samples into a fixed number K of bins. In this […]

Authors: H. Kallamadi, R. Burra, S. Mittal, S. Sharma, A. Venkatesh, A. Tandon Know more This work contributes towards the development of an efficient and scalable open-source Secure Multi-Party Computation (SMPC) protocol on machines with moderate computational resources. We use the ABY2.0 SMPC protocol implemented on the C++ based MOTION2NX framework for secure convolutional neural […]

Authors: Arun Joseph, Nikita Yadav, Vinod Ganapathy, Dushyant Behl Know more CCTV (Closed-Circuit Television) systems are commonly used for security and surveillance. They provide a visual record of events, which can be used to monitor criminal activity, support investigations, and improve public safety. Many cities have implemented a number of cameras for surveillance, with Delhi, […]

Authors: V. Walunj, V. Rajaraman, J. Dutta, A. Sharma Know more Data exchanges as Digital Public Infrastructures drive data-driven economies by enhancing efficiency, enabling revenue streams, and facilitating data monetization. This work explores integrating crypto-based payments into platforms like IUDX and ADeX, offering benefits such as enhanced security, lower fees, and decentralized control. Key focus […]

Authors: Asilata Know more This paper seeks to examine the concept of meaningfulness of consent with a focus on consent in digital transactions. To that end, it proposes a “consent matrix”, depicting the structure of consent transactions across two dimensions- the realm of consent-objects and the modes of obtaining consent. The matrix maps the two […]

Authors: Balambiga, Rohith, Srinath, Santosh, Srinivas Know more Data trusts handle data in a fiduciary capacity for data owners, allowing them to process, aggregate and share data with other stakeholders within an overarching legal and ethical framework. One of the primary challenges of data trusts is consent management. This paper characterizes the problem of consent […]

Authors: Balambiga, Srinath, Rohith, Jayati Know more Sensitive personal information of individuals and non-personal information of organizations or communities often needs to be legitimately exchanged among different stakeholders, to provide services, maintain public health, law and order, and so on. While such exchanges are necessary, they also impose enormous privacy and security challenges. Data protection […]