2 citations · 3 across the 21 of their papers we have counts for
8 papers · 1 filter
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…
Deceptive Information Retrieval
Sajani Vithana, Sennur Ulukus
We introduce the problem of deceptive information retrieval (DIR), in which a user wishes to download a required file out of multiple independent files stored in a system of databa…
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…
Private Read Update Write (PRUW) With Heterogeneous Databases
Sajani Vithana, Sennur Ulukus
We investigate the problem of private read update write (PRUW) with heterogeneous storage constrained databases in federated submodel learning (FSL). In FSL a machine learning (ML)…