37 citations · 76 across the 20 of their papers we have counts for
23 papers
Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity Resolution
Yixiang Yao, Weizhao Jin, Srivatsan Ravi
The entity resolution problem requires finding pairs across datasets that belong to different owners but refer to the same entity in the real world. To train and evaluate solutions…
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System
Weizhao Jin, Yuhang Yao, Shanshan Han +5
Federated Learning trains machine learning models on distributed devices by aggregating local model updates instead of local data. However, privacy concerns arise as the aggregated…
Evaluating the Feasibility of a Provably Secure Privacy-Preserving Entity Resolution Adaptation of PPJoin using Homomorphic Encryption
Tanmay Ghai, Yixiang Yao, Srivatsan Ravi +1
Entity resolution is the task of disambiguating records that refer to the same entity in the real world. In this work, we explore adapting one of the most efficient and accurate Ja…
Secure & Private Federated Neuroimaging
Dimitris Stripelis, Umang Gupta, Hamza Saleem +9
The amount of biomedical data continues to grow rapidly. However, collecting data from multiple sites for joint analysis remains challenging due to security, privacy, and regulator…
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
Yuhang Yao, Weizhao Jin, Srivatsan Ravi +1
Methods for training models on graphs distributed across multiple clients have recently grown in popularity, due to the size of these graphs as well as regulations on keeping data…
AMPPERE: A Universal Abstract Machine for Privacy-Preserving Entity Resolution Evaluation
Yixiang Yao, Tanmay Ghai, Srivatsan Ravi +1
Entity resolution is the task of identifying records in different datasets that refer to the same entity in the real world. In sensitive domains (e.g. financial accounts, hospital…
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Dimitris Stripelis, Hamza Saleem, Tanmay Ghai +8
Federated learning (FL) enables distributed computation of machine learning models over various disparate, remote data sources, without requiring to transfer any individual data to…
Separation and Equivalence results for the Crash-stop and Crash-recovery Shared Memory Models
Ohad Ben-Baruch, Srivatsan Ravi
Linearizability, the traditional correctness condition for concurrent data structures is considered insufficient for the non-volatile shared memory model where processes recover fo…
Programming Scalable Cloud Services with AEON
Bo Sang, Gustavo Petri, Masoud Saeida Ardekani +2
Designing low-latency cloud-based applications that are adaptable to unpredictable workloads and efficiently utilize modern cloud computing platforms is hard. The actor model is a…
Concurrency and Privacy with Payment-Channel Networks
Giulio Malavolta, Pedro Moreno-Sanchez, Aniket Kate +2
Permissionless blockchains protocols such as Bitcoin are inherently limited in transaction throughput and latency. Current efforts to address this key issue focus on off-chain paym…
On the Cost of Concurrency in Hybrid Transactional Memory
Trevor Brown, Srivatsan Ravi
State-of-the-art \emph{software transactional memory (STM)} implementations achieve good performance by carefully avoiding the overhead of \emph{incremental validation} (i.e., re-r…
Merge: An Architecture for Interconnected Testbed Ecosystems
Ryan Goodfellow, Lincoln Thurlow, Srivatsan Ravi
In the cybersecurity research community, there is no one-size-fits-all solution for merging large numbers of heterogeneous resources and experimentation capabilities from disparate…
Generalized Paxos Made Byzantine (and Less Complex)
Miguel Pires, Srivatsan Ravi, Rodrigo Rodrigues
One of the most recent members of the Paxos family of protocols is Generalized Paxos. This variant of Paxos has the characteristic that it departs from the original specification o…
A Concurrency-Optimal Binary Search Tree
Vitaly Aksenov, Vincent Gramoli, Petr Kuznetsov +2
The paper presents the first \emph{concurrency-optimal} implementation of a binary search tree (BST). The implementation, based on a standard sequential implementation of an intern…
In the Search of Optimal Concurrency
Vincent Gramoli, Petr Kuznetsov, Srivatsan Ravi
Implementing a concurrent data structure typically begins with defining its sequential specification. However, when used \emph{as is}, a nontrivial sequential data structure, such…
Progressive Transactional Memory in Time and Space
Petr Kuznetsov, Srivatsan Ravi
Transactional memory (TM) allows concurrent processes to organize sequences of operations on shared \emph{data items} into atomic transactions. A transaction may commit, in which c…
Why Transactional Memory Should Not Be Obstruction-Free
Petr Kuznetsov, Srivatsan Ravi
Transactional memory (TM) is an inherently optimistic abstraction: it allows concurrent processes to execute sequences of shared-data accesses (transactions) speculatively, with an…
A Concurrency-Optimal List-Based Set
Vitaly Aksenov, Vincent Gramoli, Petr Kuznetsov +2
Designing an efficient concurrent data structure is an important challenge that is not easy to meet. Intuitively, efficiency of an implementation is defined, in the first place, by…
On Partial Wait-Freedom in Transactional Memory
Petr Kuznetsov, Srivatsan Ravi
Transactional memory (TM) is a convenient synchronization tool that allows concurrent threads to declare sequences of instructions on shared data as speculative \emph{transactions}…
Inherent Limitations of Hybrid Transactional Memory
Dan Alistarh, Justin Kopinsky, Petr Kuznetsov +2
Several Hybrid Transactional Memory (HyTM) schemes have recently been proposed to complement the fast, but best-effort, nature of Hardware Transactional Memory (HTM) with a slow, r…
Safety of Deferred Update in Transactional Memory
Hagit Attiya, Sandeep Hans, Petr Kuznetsov +1
Transactional memory allows the user to declare sequences of instructions as speculative \emph{transactions} that can either \emph{commit} or \emph{abort}. If a transaction commits…
Optimism for Boosting Concurrency
Vincent Gramoli, Petr Kuznetsov, Srivatsan Ravi
Modern concurrent programming benefits from a large variety of synchronization techniques. These include conventional pessimistic locking, as well as optimistic techniques based on…
On the Cost of Concurrency in Transactional Memory
Petr Kuznetsov, Srivatsan Ravi
The crux of software transactional memory (STM) is to combine an easy-to-use programming interface with an efficient utilization of the concurrent-computing abilities provided by m…