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Lightweight and authentic symmetric session key cryptosystem for client–server mobile communication
Over the last decade, millions of 4G and 5G-enabled mobile devices have become part of the Internet. Almost, all the applications have been shifted...
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On Verifying Unbounded Client-Server Systems
Formal verification of Petri nets is well studied and there are existing state-of-the-art verification tools such as KREACH [5], Petrinizer [6],...
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DCM: Dynamic Client-Server Code Migration
The underlying Client/Server architecture of the Web inherently raises the question of the distribution of application logic between client and...
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Federated Unlearning and Server Right to Forget: Handling Unreliable Client Contributions
In the context of federated learning, the concept of federated unlearning has emerged, aiming to realize the “right to be forgotten”. The current...
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FLCP: federated learning framework with communication-efficient and privacy-preserving
Within the federated learning (FL) framework, the client collaboratively trains the model in coordination with a central server, while the training...
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Unbalanced private set intersection with linear communication complexity
The private set intersection (PSI) protocol allows two parties holding a set of integers to compute the intersection of their sets without revealing...
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Performance assessment and comparison of lightweight D2D-IoT communication protocols over resource constraint environment
The Internet of Things (IoT) based smart strategies are often resource constrained with respect to energy, computation and memory. Outdated...
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Rotation Key Reduction for Client-Server Systems of Deep Neural Network on Fully Homomorphic Encryption
In this paper, we propose a new concept of hierarchical rotation key for homomorphic encryption to reduce the burdens of the clients and the server...
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Single-Server Batch Delegation of Variable-Input Pairings with Unbounded Client Lifetime
Pairings are important building blocks in many public-key cryptosystems. Delegation of a pairing computation e(A, B) from a computationally weaker...
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Communication-efficient clustered federated learning via model distance
Clustered Federated Learning (CFL) leverages the differences among data distributions on clients to partition all clients into several clusters for...
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Public key versus symmetric key cryptography in client–server authentication protocols
Every month, several new protocols are pop** up, comparing themselves with a few others and claiming to outperform the whole state of the art. The...
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A Comparison of Publish-Subscribe and Client-Server Models for Streaming IoT Telemetry Data
In recent years, the Internet of Things (IoT) has become a household name both in research and commercial domains. There are numerous practical...
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Client and Server Support
The html package provides functions for processing HTTP requests. The Go template packages provide templates for generating text output with value...
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High-performance microservice differentiated domain communication technology
Microservice architecture splits the traditional monolithic application into different small services. Differences in programming language and data...
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Communication-Efficient Distributed Minimax Optimization via Markov Compression
Recently, the minimax problem has attracted a lot of attention due to its wide applications in modern machine learning fields such as GANs. With the...
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Sensing-aided peer-to-peer millimeter-wave communication
One of the bottlenecks of modern communications is to enable sensing and mutual communication simultaneously without causing scheduling conflicts,...
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Communication efficiency optimization of federated learning for computing and network convergence of 6G networks
Federated learning effectively addresses issues such as data privacy by collaborating across participating devices to train global models. However,...
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An Improved Authentication Scheme for V2I Communication
In the rapid growth of automated transportation systems Vehicle to Infrastructure (V2I) communication is growing in significance to guarantee the...
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Anomaly detection and defense techniques in federated learning: a comprehensive review
In recent years, deep learning methods based on a large amount of data have achieved substantial success in numerous fields. However, with increases...
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Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge Computing
Federated learning has emerged as a distributed learning paradigm by training at each client and aggregating at a parameter server. System...