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In Federated Learning (FL), many privacy-enhancing techniques, such as secure aggregation and distributed differential privacy, provide security guarantees under the assumption of having an honest majority among participants. However, an adversarial ...

Relaxing strong consistency plays a vital role in achieving scalability and availability for geo-replicated web applications. However, making relaxation correct in modern implementations, typically written in dynamic languages and utilizing high-level ...

Federated learning (FL) is increasingly deployed among multiple clients to train a shared model over decentralized data. To address privacy concerns, FL systems need to safeguard the clients' data from disclosure during training and control data leakage ...

Many organizations own data but have limited machine learning expertise (data owners). On the other hand, organizations that have expertise need data from diverse sources to train truly generalizable models (model owners). With the advancement of ...

Gradient compression is a promising approach to alleviating the communication bottleneck in data parallel deep neural network (DNN) training by significantly reducing the data volume of gradients for synchronization. While gradient compression is being ...

Serverless computing is increasingly seen as a pivot cloud computing paradigm that has great potential to simplify application development while removing the burden of operational tasks from developers. Despite these advantages, the use of serverless ...

Serverless computing has emerged as a new cloud computing paradigm, where an application consists of individual functions that can be separately managed and executed. However, the function development environment of all serverless computing frameworks ...

A distributed join is a fundamental operation for processing massive datasets in parallel. Unfortunately, computing an equi-join over such datasets is very resource-intensive, even when done in parallel. Given this cost, the equi-join operator becomes a ...

Serverless computing has emerged as a new cloud computing paradigm, where an application consists of individual functions that can be separately managed and executed. However, existing serverless platforms normally isolate and execute functions in ...

Approximate computing aims for efficient execution of workflows where an approximate output is sufficient instead of the exact output. The idea behind approximate computing is to compute over a representative sample instead of the entire input dataset. ...

Major cloud computing operators provide powerful monitoring tools to understand the current (and prior) state of the distributed systems deployed in their infrastructure. While such tools provide a detailed monitoring mechanism at scale, they also pose ...

A common practice to increase the reliability of a cloud application is to deploy redundant instances. Unfortunately such redundancy efforts can be undermined if the application's instances share common dependencies. This paper presents ReCloud, a novel ...

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing?

To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream ...

By publishing papers together, academic authors can form a co-authorship network, modeling the collaboration among them. This paper presents a data-driven study by crawling and analyzing the vast majority of author profiles of Google Scholar. We make ...

Estimating statistical information about the most recent parts of a stream is an important problem in network and cloud monitoring. Modern cloud infrastructures generate in high volume and high velocity various measurements on CPU, memory and storage ...

Reputation systems help users evaluate information quality and incentivize civilized behavior, often by tallying feedback from other users such as "likes" or votes and linking these scores to a user's long-term identity. This identity linkage enables ...

Today's systems pervasively rely on redundancy to ensure reliability. In complex multi-layered hardware/software stacks, however - especially in the clouds where many independent businesses deploy interacting services on common infrastructure - ...

To enhance the reliability of cloud services, many application providers leverage multiple cloud providers for redundancy. Unfortunately, such techniques fail to recognize that seemingly independent redundant clouds may share third-party infrastructure ...

There is a growing body of research on mechanisms for preserving online user privacy while still allowing aggregate queries over private user data. A common approach is to store user data at users' devices, and to query the data in such a way that a ...

Active Peer-to-Peer (P2P) worms present serious threats to the global Internet by exploiting popular P2P applications to perform rapid topological self-propagation. Active P2P worms pose more deadly threats than normal scanning worms because they do not ...