Post-Quantum Key Exchange Protocols

If an eavesdropper Eve is equipped with quantum computers, she can easily break the public key exchange protocols used today. In this paper we will discuss the post-quantum Diffie-Hellman key exchange and private key exchange protocols.Comment: 11 pages, 2 figures. Submitted to SPIE DSS 2006; v2 citation typos fixed; v3 appendix typos correcte

The Bounded Storage Model in The Presence of a Quantum Adversary

An extractor is a function E that is used to extract randomness. Given an imperfect random source X and a uniform seed Y, the output E(X,Y) is close to uniform. We study properties of such functions in the presence of prior quantum information about X, with a particular focus on cryptographic applications. We prove that certain extractors are suitable for key expansion in the bounded storage model where the adversary has a limited amount of quantum memory. For extractors with one-bit output we show that the extracted bit is essentially equally secure as in the case where the adversary has classical resources. We prove the security of certain constructions that output multiple bits in the bounded storage model.Comment: 13 pages Latex, v3: discussion of independent randomizers adde

Circuit Amortization Friendly Encodings and their Application to Statistically Secure Multiparty Computation

At CRYPTO 2018, Cascudo et al. introduced Reverse Multiplication Friendly Embeddings (RMFEs). These are a mechanism to compute $\delta$ parallel evaluations of the same arithmetic circuit over a field $\mathbb{F}_q$ at the cost of a single evaluation of that circuit in $\mathbb{F}_{q^d}$, where $\delta < d$. Due to this inequality, RMFEs are a useful tool when protocols require to work over $\mathbb{F}_{q^d}$ but one is only interested in computing over $\mathbb{F}_q$. In this work we introduce Circuit Amortization Friendly Encodings (CAFEs), which generalize RMFEs while having concrete efficiency in mind. For a Galois Ring $R = GR(2^{k}, d)$, CAFEs allow to compute certain circuits over $\mathbb{Z}_{2^k}$ at the cost of a single secure multiplication in $R$. We present three CAFE instantiations, which we apply to the protocol for MPC over $\mathbb{Z}_{2^k}$ via Galois Rings by Abspoel et al. (TCC 2019). Our protocols allow for efficient switching between the different CAFEs, as well as between computation over $GR(2^{k}, d)$ and $\mathbb{F}_{2^{d}}$ in a way that preserves the CAFE in both rings. This adaptability leads to efficiency gains for e.g. Machine Learning applications, which can be represented as highly parallel circuits over $\mathbb{Z}_{2^k}$ followed by bit-wise operations. From an implementation of our techniques, we estimate that an SVM can be evaluated on 250 images in parallel up to $\times 7$ more efficiently using our techniques, compared to the protocol from Abspoel et al. (TCC 2019)

FinBook: literary content as digital commodity

This short essay explains the significance of the FinBook intervention, and invites the reader to participate. We have associated each chapter within this book with a financial robot (FinBot), and created a market whereby book content will be traded with financial securities. As human labour increasingly consists of unstable and uncertain work practices and as algorithms replace people on the virtual trading floors of the worlds markets, we see members of society taking advantage of FinBots to invest and make extra funds. Bots of all kinds are making financial decisions for us, searching online on our behalf to help us invest, to consume products and services. Our contribution to this compilation is to turn the collection of chapters in this book into a dynamic investment portfolio, and thereby play out what might happen to the process of buying and consuming literature in the not-so-distant future. By attaching identities (through QR codes) to each chapter, we create a market in which the chapter can ‘perform’. Our FinBots will trade based on features extracted from the authors’ words in this book: the political, ethical and cultural values embedded in the work, and the extent to which the FinBots share authors’ concerns; and the performance of chapters amongst those human and non-human actors that make up the market, and readership. In short, the FinBook model turns our work and the work of our co-authors into an investment portfolio, mediated by the market and the attention of readers. By creating a digital economy specifically around the content of online texts, our chapter and the FinBook platform aims to challenge the reader to consider how their personal values align them with individual articles, and how these become contested as they perform different value judgements about the financial performance of each chapter and the book as a whole. At the same time, by introducing ‘autonomous’ trading bots, we also explore the different ‘network’ affordances that differ between paper based books that’s scarcity is developed through analogue form, and digital forms of books whose uniqueness is reached through encryption. We thereby speak to wider questions about the conditions of an aggressive market in which algorithms subject cultural and intellectual items – books – to economic parameters, and the increasing ubiquity of data bots as actors in our social, political, economic and cultural lives. We understand that our marketization of literature may be an uncomfortable juxtaposition against the conventionally-imagined way a book is created, enjoyed and shared: it is intended to be