What makes consent meaningful?
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
June 2024 What makes consent meaningful? Authors: Asilata 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 dimensions …
Continue Reading
Consent Service Architecture for Policy-Based Consent Management in Data Trusts
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
Jan 2024 Consent Service Architecture for Policy-Based Consent Management in Data Trusts Authors: Balambiga, Rohith, Srinath, Santosh, Srinivas 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 …
Continue Reading
Extensible Consent Management Architectures for Data Trusts
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
Sep 2023 Extensible Consent Management Architectures for Data Trusts Authors: Balambiga, Srinath, Rohith, Jayati 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. …
Continue Reading
Graphiti: Secure Graph Computation Made More Scalable
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
December 2024 Graphiti: Secure Graph Computation Made More Scalable Authors: Koti, N., Kukkala, V. B., Patra, A., & Raj Gopal, B. Privacy-preserving graph analysis allows performing computations on graphs that store sensitive information, while ensuring all the information about the topology of the graph as well as data associated with the nodes and edges remains hidden. The current work addresses …
Continue Reading
Ruffle: Rapid 3-party shuffle protocols
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
March 2023 Ruffle: Rapid 3-party shuffle protocols Authors: Koti, N., Kukkala, V. B., Patra, A., Gopal, B. R., & Sangal, S Secure shuffle is an important primitive that finds use in several applications such as secure electronic voting, oblivious RAMs, secure sorting, to name a few. For time-sensitive shuffle-based applications that demand a fast response time, it is essential to …
Continue Reading
Vogue: Faster computation of private heavy hitters
-
CDPG
-
January 10, 2025
-
Data Privacy
-
0 Comments
October 2023 Vogue: Faster computation of private heavy hitters Authors: Jangir, P., Koti, N., Kukkala, V. B., Patra, A., Gopal, B. R., & Sangal, S Consider the problem of securely identifying τ -heavy hitters, where given a set of client inputs, the goal is to identify those inputs which are held by at least τ clients in a privacy-preserving manner. …
Continue Reading
Shield: Secure Allegation Escrow System with Stronger Guarantees
-
CDPG
-
January 9, 2025
-
Data Privacy
-
0 Comments
April 2023 Shield: Secure Allegation Escrow System with Stronger Guarantees Authors: Koti, N., Kukkala, V. B., Patra, A., & Gopal, B. R The rising issues of harassment, exploitation, corruption, and other forms of abuse have led victims to seek comfort by acting in unison against common perpetrators (e.g., #MeToo movement). One way to curb these issues is to install allegation …
Continue Reading
Find thy neighbourhood: Privacy-preserving local clustering.
-
CDPG
-
January 9, 2025
-
Data Privacy
-
0 Comments
December 2022 Find thy neighbourhood: Privacy-preserving local clustering Authors: Koti, Nishat, Varsha Bhat Kukkala, Arpita Patra, and Bhavish Raj Gopal Identifying a cluster around a seed node in a graph, termed local clustering, finds use in several applications, including fraud detection, targeted advertising, community detection, etc. However, performing local clustering is challenging when the graph is distributed among multiple data …
Continue Reading
Pentagod: Stepping beyond traditional god with five parties
-
CDPG
-
January 9, 2025
-
Data Privacy
-
0 Comments
Aug 2022 Pentagod: Stepping beyond traditional god with five parties Authors: Koti, N., Kukkala, V. B., Patra, A., & Raj Gopal, B. Secure multiparty computation (MPC) is increasingly being used to address privacy issues in various applications. The recent work of Alon et al. (CRYPTO’20) identified the shortcomings of traditional MPC and defined a Friends-and-Foes (FaF) security notion to address …
Continue Reading
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
-
CDPG
-
January 9, 2025
-
Data Privacy
-
0 Comments
December 2023 Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators Authors: Prashanthi S.K., Vinayaka Hegde, Keerthana Patchava, Ankita Das and Yogesh Simmhan Edge devices have typically been used for DNN in-ferencing. The increase in the compute power of accelerated edges is leading to their use in DNN training also. As privacy becomes a concern on multi-tenant edge …
Continue Reading