Public key cryptosystems : theory, application and implementation

The determination of an individual's right to privacy is mainly a nontechnical matter, but the pragmatics of providing it is the central concern of the cryptographer. This thesis has sought answers to some of the outstanding issues in cryptography. In particular, some of the theoretical, application and implementation problems associated with a Public Key Cryptosystem (PKC).The Trapdoor Knapsack (TK) PKC is capable of fast throughput, but suffers from serious disadvantages. In chapter two a more general approach to the TK-PKC is described, showing how the public key size can be significantly reduced. To overcome the security limitations a new trapdoor was described in chapter three. It is based on transformations between the radix and residue number systems.Chapter four considers how cryptography can best be applied to multi-addressed packets of information. We show how security or communication network structure can be used to advantage, then proposing a new broadcast cryptosystem, which is more generally applicable.Copyright is traditionally used to protect the publisher from the pirate. Chapter five shows how to protect information when in easily copyable digital format.Chapter six describes the potential and pitfalls of VLSI, followed in chapter seven by a model for comparing the cost and performance of VLSI architectures. Chapter eight deals with novel architectures for all the basic arithmetic operations. These architectures provide a basic vocabulary of low complexity VLSI arithmetic structures for a wide range of applications.The design of a VLSI device, the Advanced Cipher Processor (ACP), to implement the RSA algorithm is described in chapter nine. It's heart is the modular exponential unit, which is a synthesis of the architectures in chapter eight. The ACP is capable of a throughput of 50 000 bits per second

X-Rel: Energy-Efficient and Low-Overhead Approximate Reliability Framework for Error-Tolerant Applications Deployed in Critical Systems

Triple Modular Redundancy (TMR) is one of the most common techniques in fault-tolerant systems, in which the output is determined by a majority voter. However, the design diversity of replicated modules and/or soft errors that are more likely to happen in the nanoscale era may affect the majority voting scheme. Besides, the significant overheads of the TMR scheme may limit its usage in energy consumption and area-constrained critical systems. However, for most inherently error-resilient applications such as image processing and vision deployed in critical systems (like autonomous vehicles and robotics), achieving a given level of reliability has more priority than precise results. Therefore, these applications can benefit from the approximate computing paradigm to achieve higher energy efficiency and a lower area. This paper proposes an energy-efficient approximate reliability (X-Rel) framework to overcome the aforementioned challenges of the TMR systems and get the full potential of approximate computing without sacrificing the desired reliability constraint and output quality. The X-Rel framework relies on relaxing the precision of the voter based on a systematical error bounding method that leverages user-defined quality and reliability constraints. Afterward, the size of the achieved voter is used to approximate the TMR modules such that the overall area and energy consumption are minimized. The effectiveness of employing the proposed X-Rel technique in a TMR structure, for different quality constraints as well as with various reliability bounds are evaluated in a 15-nm FinFET technology. The results of the X-Rel voter show delay, area, and energy consumption reductions of up to 86%, 87%, and 98%, respectively, when compared to those of the state-of-the-art approximate TMR voters.Comment: This paper has been published in IEEE Transactions on Very Large Scale Integration (VLSI) System

Spatial-photonic Boltzmann machines: low-rank combinatorial optimization and statistical learning by spatial light modulation

The spatial-photonic Ising machine (SPIM) [D. Pierangeli et al., Phys. Rev. Lett. 122, 213902 (2019)] is a promising optical architecture utilizing spatial light modulation for solving large-scale combinatorial optimization problems efficiently. However, the SPIM can accommodate Ising problems with only rank-one interaction matrices, which limits its applicability to various real-world problems. In this Letter, we propose a new computing model for the SPIM that can accommodate any Ising problem without changing its optical implementation. The proposed model is particularly efficient for Ising problems with low-rank interaction matrices, such as knapsack problems. Moreover, the model acquires learning ability and can thus be termed a spatial-photonic Boltzmann machine (SPBM). We demonstrate that learning, classification, and sampling of the MNIST handwritten digit images are achieved efficiently using SPBMs with low-rank interactions. Thus, the proposed SPBM model exhibits higher practical applicability to various problems of combinatorial optimization and statistical learning, without losing the scalability inherent in the SPIM architecture.Comment: 7 pages, 5 figures (with a 3-page supplemental

L'intertextualité dans les publications scientifiques

La base de données bibliographiques de l'IEEE contient un certain nombre de duplications avérées avec indication des originaux copiés. Ce corpus est utilisé pour tester une méthode d'attribution d'auteur. La combinaison de la distance intertextuelle avec la fenêtre glissante et diverses techniques de classification permet d'identifier ces duplications avec un risque d'erreur très faible. Cette expérience montre également que plusieurs facteurs brouillent l'identité de l'auteur scientifique, notamment des collectifs de chercheurs à géométrie variable et une forte dose d'intertextualité acceptée voire recherchée