2 citations · 2 across the 7 of their papers we have counts for
7 papers
Private Membership Aggregation
Mohamed Nomeir, Sajani Vithana, Sennur Ulukus
We consider the problem of private membership aggregation (PMA), in which a user counts the number of times a certain element is stored in a system of independent parties that stor…
Quantum Symmetric Private Information Retrieval with Secure Storage and Eavesdroppers
Alptug Aytekin, Mohamed Nomeir, Sajani Vithana +1
We consider both the classical and quantum variations of -secure, -eavesdropped and -colluding symmetric private information retrieval (SPIR). This is the first work to st…
Information-Theoretically Private Federated Submodel Learning with Storage Constrained Databases
Sajani Vithana, Sennur Ulukus
In federated submodel learning (FSL), a machine learning model is divided into multiple submodels based on different types of data used for training. Each user involved in the trai…
Asymmetric -Secure -Private Information Retrieval: More Databases is Not Always Better
Mohamed Nomeir, Sajani Vithana, Sennur Ulukus
We consider a special case of -secure -private information retrieval (XSTPIR), where the security requirement is \emph{asymmetric} due to possible missing communication links…
Private Information Retrieval and Its Applications: An Introduction, Open Problems, Future Directions
Sajani Vithana, Zhusheng Wang, Sennur Ulukus
Private information retrieval (PIR) is a privacy setting that allows a user to download a required message from a set of messages stored in a system of databases without revealing…
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top Sparsification
Sajani Vithana, Sennur Ulukus
In federated learning (FL), a machine learning (ML) model is collectively trained by a large number of users, using their private data in their local devices. With top sparsifi…