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Gradient descent (GD) methods are commonly employed in machine learning problems to optimize the parameters of the model in an iterative fashion. For problems with massive datasets, computations are distributed to many parallel computing…

Information Theory · Computer Science 2019-03-06 Emre Ozfatura , Deniz Gunduz , Sennur Ulukus

In this paper, we present an achievable security scheme for an interference channel with arbitrary number of users. In this model, each receiver should be able to decode its intended message while it cannot decode any meaningful information…

Cryptography and Security · Computer Science 2020-04-20 Parisa Babaheidarian , Somayeh Salimi , Panos Papadimitratos

Existing gradient coding schemes introduce identical redundancy across the coordinates of gradients and hence cannot fully utilize the computation results from partial stragglers. This motivates the introduction of diverse redundancies…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-21 Qi Wang , Ying Cui , Chenglin Li , Junni Zou , Hongkai Xiong

We construct general schemes for multi-partite quantum secret sharing using multi-level systems, and find that the consistent conditions for valid measurements can be summarized in two simple algebraic conditions. The scheme using the very…

Quantum Physics · Physics 2015-07-22 I-Ching Yu , Feng-Li Lin , Ching-Yu Huang

Key establishment in sensor networks becomes a challenging problem because of the resource limitations of the sensors and also due to vulnerability to physical capture of the sensor nodes. In this paper, we propose an unconditionally secure…

Cryptography and Security · Computer Science 2011-03-25 Ashok Kumar Das

Index coding is concerned with efficient broadcast of a set of messages to receivers in the presence of receiver side information. In this paper, we study the secure index coding problem with security constraints on the receivers…

Information Theory · Computer Science 2020-04-16 Yucheng Liu , Parastoo Sadeghi , Neda Aboutorab , Arman Sharififar

We consider unreliable distributed learning systems wherein the training data is kept confidential by external workers, and the learner has to interact closely with those workers to train a model. In particular, we assume that there exists…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-10 Lili Su , Jiaming Xu

Providing security for messages in group communication is more essential and critical nowadays. In group oriented applications such as Video conferencing and entertainment applications, it is necessary to secure the confidential data in…

Cryptography and Security · Computer Science 2012-12-13 R. Velumadhava Rao , K. Selvamani , R. Elakkiya

In this paper, a new key-agreement scheme is proposed and analyzed. In addition to being provably secure in shared secret key indistinguishability model, the scheme has an interesting feature: while using exponentiation over a cyclic…

Cryptography and Security · Computer Science 2021-06-08 Abdelhaliem Babiker

This paper studies the fundamental limits of the shared-link coded caching problem with correlated files, where a server with a library of $N$ files communicates with $K$ users who can locally cache $M$ files. Given an integer $r \in [N]$,…

Information Theory · Computer Science 2021-06-15 Kai Wan , Daniela Tuninetti , Mingyue Ji , Giuseppe Caire

We consider a secure communication scenario through the two-user Gaussian interference channel: each transmitter (user) has a confidential message to send reliably to its intended receiver while keeping it secret from the other receiver.…

Information Theory · Computer Science 2016-04-26 Parisa Babaheidarian , Somayeh Salimi , Panos Papadimitratos

For a multi-source multi-terminal noiseless network, the key-dissemination problem involves the task of multicasting a secret key K from the network sources to its terminals. As in secure multicast network-coding, in the key-dissemination…

Information Theory · Computer Science 2022-05-20 Michael Langberg , Michelle Effros

In distributed computing, slower nodes (stragglers) usually become a bottleneck. Gradient Coding (GC), introduced by Tandon et al., is an efficient technique that uses principles of error-correcting codes to distribute gradient computation…

Machine Learning · Computer Science 2023-06-29 M. Nikhil Krishnan , MohammadReza Ebrahimi , Ashish Khisti

We consider a generalization of the gradient coding framework where a dataset is divided across $n$ workers and each worker transmits to a master node one or more linear combinations of the gradients over its assigned data subsets. Unlike…

Information Theory · Computer Science 2022-05-03 Sahasrajit Sarmasarkar , V. Lalitha , Nikhil Karamchandani

Three closely-related polynomial-based group key pre-distribution schemes have recently been proposed, aimed specifically at wireless sensor networks. The schemes enable any subset of a predefined set of sensor nodes to establish a shared…

Cryptography and Security · Computer Science 2026-03-20 Chris J Mitchell

Several recently proposed code-based cryptosystems base their security on a slightly generalized version of the classical (syndrome) decoding problem. Namely, in the so-called restricted (syndrome) decoding problem, the error values stem…

Cryptography and Security · Computer Science 2023-06-09 Marco Baldi , Sebastian Bitzer , Alessio Pavoni , Paolo Santini , Antonia Wachter-Zeh , Violetta Weger

The compound secure groupcast problem is considered, where the key variables at $K$ receivers are designed so that a transmitter can securely groupcast a message to any $N$ out of the $K$ receivers through a noiseless broadcast channel. The…

Information Theory · Computer Science 2020-05-01 Hua Sun

It was recently observed in [1], that in index coding, learning the coding matrix used by the server can pose privacy concerns: curious clients can extract information about the requests and side information of other clients. One approach…

Information Theory · Computer Science 2018-10-16 Mohammed Karmoose , Linqi Song , Martina Cardone , Christina Fragouli

We consider distributed learning in the presence of slow and unresponsive worker nodes, referred to as stragglers. In order to mitigate the effect of stragglers, gradient coding redundantly assigns partial computations to the worker such…

Information Theory · Computer Science 2022-12-19 Luis Maßny , Christoph Hofmeister , Maximilian Egger , Rawad Bitar , Antonia Wachter-Zeh

We consider a Gaussian multiple access channel with $K$ transmitters, a (intended) receiver and an external eavesdropper. The transmitters wish to reliably communicate with the receiver while concealing their messages from the eavesdropper.…

Cryptography and Security · Computer Science 2015-04-23 Parisa Babaheidarian , Somayeh Salimi