A Quantum Multiparty Packing Lemma and the Relay Channel

Optimally encoding classical information in a quantum system is one of the oldest and most fundamental challenges of quantum information theory. Holevo's bound places a hard upper limit on such encodings, while the Holevo-Schumacher-Westmoreland (HSW) theorem addresses the question of how many classical messages can be "packed" into a given quantum system. In this article, we use Sen's recent quantum joint typicality results to prove a one-shot multiparty quantum packing lemma generalizing the HSW theorem. The lemma is designed to be easily applicable in many network communication scenarios. As an illustration, we use it to straightforwardly obtain quantum generalizations of well-known classical coding schemes for the relay channel: multihop, coherent multihop, decode-forward, and partial decode-forward. We provide both finite blocklength and asymptotic results, the latter matching existing classical formulas. Given the key role of the classical packing lemma in network information theory, our packing lemma should help open the field to direct quantum generalization.Comment: 20 page

Network information theory for classical-quantum channels

Network information theory is the study of communication problems involving multiple senders, multiple receivers and intermediate relay stations. The purpose of this thesis is to extend the main ideas of classical network information theory to the study of classical-quantum channels. We prove coding theorems for quantum multiple access channels, quantum interference channels, quantum broadcast channels and quantum relay channels. A quantum model for a communication channel describes more accurately the channel's ability to transmit information. By using physically faithful models for the channel outputs and the detection procedure, we obtain better communication rates than would be possible using a classical strategy. In this thesis, we are interested in the transmission of classical information, so we restrict our attention to the study of classical-quantum channels. These are channels with classical inputs and quantum outputs, and so the coding theorems we present will use classical encoding and quantum decoding. We study the asymptotic regime where many copies of the channel are used in parallel, and the uses are assumed to be independent. In this context, we can exploit information-theoretic techniques to calculate the maximum rates for error-free communication for any channel, given the statistics of the noise on that channel. These theoretical bounds can be used as a benchmark to evaluate the rates achieved by practical communication protocols. Most of the results in this thesis consider classical-quantum channels with finite dimensional output systems, which are analogous to classical discrete memoryless channels. In the last chapter, we will show some applications of our results to a practical optical communication scenario, in which the information is encoded in continuous quantum degrees of freedom, which are analogous to classical channels with Gaussian noise.Comment: Ph.D. Thesis, McGill University, School of Computer Science, July 2012, 223 pages, 18 figures, 36 TikZ diagram

MPC for Everyone

The age of internet of things, where each device and application double up as a source of data has led to an unprecedented influx of data and analyzing this data is becoming increasingly useful. Given its sensitive nature, there is a growing demand for better and more efficient data collection and computation techniques that respect privacy. Most existing techniques for privacy-preserving computations incur large overheads, limiting platforms that can be used for performing such heavy-duty computations. Moreover, using such platforms for all computations, accumulates power with organizations that own these platforms and creates central targets of failure. This necessitates the need for distributing work and power when computing on private data. Powerful and well-studied cryptographic notions such as secure multiparty computation (MPC) help distribute power by enabling privacy-preserving collaboration between mutually distrusting entities for complex computations on data. Unfortunately, modern MPC protocols have unaccommodating participation models. In general, parties participating in such protocols are required to perform large computations and are expected to stay active throughout the execution. However, unlike large organizations, not everyone might have the resources to carry out such large-scale and long-drawn computations. In this dissertation, our goal is to democratize such computations by designing MPC protocols that empower regular people and smaller organizations to emulate large-scale computations in a distributed manner. We make progress in two different directions. In the first part of this dissertation, we incentivize more participation in an MPC protocol by effectively “distributing” the work amongst parties. In most known protocols, computation and communication amongst parties increases as the number of participants increase. We propose a new MPC protocol, where the per-party work decreases as the number of parties increase. As a result, when run with a large number of parties, the burden on each individual participant is significantly reduced – enabling efficient large-scale MPC computations, involving hundreds and thousands of participants. Including more participants also dilutes the power of each individual party, which is highly desirable. In the second part of this dissertation, we introduce a new participation model called Fluid MPC. Unlike all existing protocols, where participants are required to remain online throughout the execution, in this model, one can design protocols that allow parties to leave and join the protocol execution as they wish. The minimum amount of work that a party is required to do in order to participate is extremely small in comparison to the size of the entire computation. This extreme flexibility allows parties – including those with low resources and limited time – to contribute according to their computational capacity and effectively yields a weighted, privacy-preserving, distributed computing system

Scalable and Robust Distributed Algorithms for Privacy-Preserving Applications

We live in an era when political and commercial entities are increasingly engaging in sophisticated cyber attacks to damage, disrupt, or censor information content and to conduct mass surveillance. By compiling various patterns from user data over time, untrusted parties could create an intimate picture of sensitive personal information such as political and religious beliefs, health status, and so forth. In this dissertation, we study scalable and robust distributed algorithms that guarantee user privacy when communicating with other parties to either solely exchange information or participate in multi-party computations. We consider scalability and robustness requirements in three privacy-preserving areas: secure multi-party computation (MPC), anonymous broadcast, and blocking-resistant Tor bridge distribution. We propose decentralized algorithms for MPC that, unlike most previous work, scale well with the number of parties and tolerate malicious faults from a large fraction of the parties. Our algorithms do not require any trusted party and are fully load-balanced. Anonymity is an essential tool for achieving privacy; it enables individuals to communicate with each other without being identified as the sender or the receiver of the information being exchanged. We show that our MPC algorithms can be effectively used to design a scalable anonymous broadcast protocol. We do this by developing a multi-party shuffling protocol that can efficiently anonymize a sequence of messages in the presence of many faulty nodes. Our final approach for preserving user privacy in cyberspace is to improve Tor; the most popular anonymity network in the Internet. A current challenge with Tor is that colluding corrupt users inside a censorship territory can completely block user\u27s access to Tor by obtaining information about a large fraction of Tor bridges; a type of relay nodes used as the Tor\u27s primary mechanism for blocking-resistance. We describe a randomized bridge distribution algorithm, where all honest users are guaranteed to connect to Tor in the presence of an adversary corrupting an unknown number of users. Our simulations suggest that, with minimal resource costs, our algorithm can guarantee Tor access for all honest users after a small (logarithmic) number of rounds

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing