Instantiability of RSA-OAEP Under Chosen-Plaintext Attack

We show that the widely deployed RSA-OAEP encryption scheme of Bellare and Rogaway (Eurocrypt 1994), which combines RSA with two rounds of an underlying Feistel network whose hash ( i.e., round) functions are modeled as random oracles, meets indistinguishability under chosen-plaintext attack (IND-CPA) in the standard model based on simple, non-interactive, and non-interdependent assumptions on RSA and the hash functions. To prove this, we first give a result on a more general notion called “padding-based” encryption, saying that such a scheme is IND-CPA if (1) its underlying padding transform satisfies a “fooling" condition against small-range distinguishers on a class of high-entropy input distributions, and (2) its trapdoor permutation is sufficiently lossy as defined by Peikert and Waters (STOC 2008). We then show that the first round of OAEP satisfies condition (1) if its hash function is t-wise independent for t roughly proportional to the allowed message length. We clarify that this result requires the hash function to be keyed, and for its key to be included in the public key of RSA-OAEP. We also show that RSA satisfies condition (2) under the \(\Phi \)-Hiding Assumption of Cachin et al. (Eurocrypt 1999). This is the first positive result about the instantiability of RSA-OAEP. In particular, it increases confidence that chosen-plaintext attacks are unlikely to be found against the scheme. In contrast, RSA-OAEP’s predecessor in PKCS #1 v1.5 was shown to be vulnerable to such attacks by Coron et al. (Eurocrypt 2000).     

Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin

This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all bitcoins in existence represent approximately $7 billion, and more than $60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.Using cross-sectional empirical data examining 66 of the most widely used cryptocurrencies, a regression model was estimated that points to three main drivers of cryptocurrency value: the level of competition in the network of producers, the rate of unit production, and the difficulty of algorithm used to “mine” for the cryptocurrency. These amount to relative differences in the cost of production of one digital currency over another at the margin, pointing to differences in relative cost of production – electricity goes in, cryptocurrency comes out. Using that as a starting point, a no-arbitrage situation is established for Bitcoin-like cryptocurrencies followed by the formalization of a cost of production model to determine the fair value of a bitcoin.     

Fast and Compact 16 by 16 Cellular Neural Network Implementation

The paper presents a Cellular Neural Network implementation based on a high gain sigmoid operation. The required simplifications to the original theory are described that allow the use of high gain. With this design black and white images can be processed. The basic building blocks in a cell are described. A 16×16 cells network has been designed and processed with 1.2 micron CMOS technology. Measurement results which show the operation of the network are presented.     

Dynamic resource allocation in OFDM systems: an overview of cross-layer optimization principles and techniques

Recently, a lot of research effort has been spent on cross-layer system design. It has been shown that cross-layer mechanisms (i.e., policies) potentially provide significant performance gains for various systems. In this article we review several aspects of cross-layer system optimization regarding wireless OFDM systems. We discuss basic optimization models and present selected heuristic approaches realizing cross-layer policies by means of dynamic resource allocation. Two specific areas are treated separately: models and dynamic approaches for single transmitter/receiver pairs (i.e., a point-to-point communication scenario) as well as models and approaches for point-to-multipoint communication scenarios (e.g., the downlink of a wireless cell). This article provides basic knowledge in order to investigate future OFDM cross-layer-optimization issues     

High-speed photoconductive switch based on low-temperature GaAs transferred on SiO/sub 2/-Si substrate

In this letter, we report high-speed photoconductive switches based on low-temperature (LT) grown GaAs on Si substrate. Epitaxially grown LT GaAs was separated from its substrate, transferred on an SiO/sub 2/-coated Si substrate and integrated with a transmission line. The 10/spl times/20-/spl mu/m/sup 2/ switches exhibit high breakdown voltage and low dark currents (<10/sup -7/ A at 100 V). The photoresponse at 810 nm shows electrical transients with /spl sim/0.55-ps full-width at half-maximum and /spl sim/0.37-ps decay time, both independent on the bias voltage up to the tested limit of 120 V. The photoresponse amplitude increases up to /spl sim/0.7 V with increased bias and the signal bandwith is /spl sim/500 GHz. The freestanding LT GaAs switches are best suited for ultrafast optoelectronic testing since they can be placed at virtually any point on the test circuit.     

Finding the dominant source of distortion in two-stage op-amps

Although non-linear distortion is an important specification for op-amps, it is only determined at the end of the design in classical design flows, leaving the designers without a clue about its origin. Recently, the Best Linear Approximation (BLA) has been introduced to approximate non-linear systems. It allows to describe the behaviour of a non-linear system as a linear Frequency Response Function combined with a coloured noise source to describe respectively the wanted linear response and the distortion. To determine the dominant source of non-linear distortion, we combine the BLA with a classical noise analysis in this paper. The paper explains the BLA-based noise analysis and shows the result of this simulation-based analysis when applied to various op-amp architectures. The analysis pinpoints the non-linear hot-spots in an efficient way, without the use of special simulations, manual analytical calculations or modified transistor models.     

面对高亮度LED设计的挑战

现在全球各地已逐渐淘汰传统的白炽灯泡.不仅政府机构,连民间使用者也要求更高效率的照明解决方案.精致型荧光灯泡(CFL)并非解决此项问题的最佳方案.     

Hybrid image steganography method using Lempel Ziv Welch and genetic algorithms for hiding confidential data

Multidimensional Systems and Signal Processing - Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the...     

Blind deconvolution of ultrasound sequences using nonparametric local polynomial estimates of the pulse

The problem of reconstructing the reflectivity of a biological tissue is examined by means of blind deconvolution of the echo ultrasound signals. It is shown that the quality of the reconstruction procedure can be significantly improved when initially the ultrasonic pulse is accurately estimated. A new approach to the estimation of the ultrasound pulse echo sequences is proposed, using local polynomial approximation, which is closely related to the wavelet transform theory. This approach can be viewed as a modification of homomorphic deconvolution, by using bases different from the Fourier basis of the space of square-integrable functions L2. The bases used here are the orthogonal compactly supported wavelet bases. It is shown that the locality of the estimate can be extremely useful in number of cases of practical interest, resulting in estimates with smaller root-mean squared (rms) errors, as compared with estimates employing the Fourier basis. This approach is applied to ultrasound signals, for estimation of the ultrasound pulse log-spectrum from the log-spectrum of radio-frequency (RF) sequences. It is shown, conceptually and experimentally, that the proposed approach can provide robust and rapidly computed estimates of the ultrasound pulses from the RF-sequences, as obtained in the process of tissue scanning. The pulse phase was recovered using the minimum-phase assumption, which was found to hold for the transducers in use. The obtained pulse estimates are used for the deconvolution of the RF-sequences, which result in stable estimates of the tissue reflectivity function, fairly independent of the properties of the imaging system. Simulated data, data obtained from several phantoms and from in vitro experiments have been processed and the results seem to be quite promising.     

Combinatorial auctions for exchanging resources over a grid network

In grid systems, users compete for different types of resources such that they may execute their applications. Traditional grid systems are formed of organisations that join together for the purpose of collaborative projects. Resources of each of the participating organisation are pooled such that members of individual organisations may access the shared infrastructure. In general, each participant is both a provider and a consumer of resources. Whilst such systems address large organisations, in this paper we address democratic grid systems to satisfy needs of small organisations and even individuals, where on-demand grids may be formed by drawing idling resources available on the Internet. Whilst traditional grid systems resort to allocations that satisfy system specific objectives such as maximization of the resource utilisation, market mechanisms try to obtain allocations that are efficient economically. Economic mechanisms permit to achieve equilibrium between supply and demand and furthermore provide incentives for providers. Combinatorial auction has been argued as an effective mechanism to address the problem of resource allocation within grid systems. Auctions within which multiple types of resources in varying quantities may be traded eliminate the exposure problem by addressing co-allocation. In this paper, we describe a combinatorial exchange where multiple providers and multiple consumers may participate. We describe the winner determination problem that incorporates the time dimension, i.e. resource bundles may be requested for different time ranges, and describe a set of heuristics that have been designed to be fast. We show that these achieve a high level of efficiency as compared to exact solutions. The second part focusses on the pricing problem. The objective is to compute prices that represent the state of the market and bring trustworthy feedback to participants. Drawing on the approach taken by Kwasnica et al. (Manage Sci 51(3):419–434, 2005), we propose a pricing model that computes per-item pricing. Per-item pricing allows users to deduce the price of bundles that they require by linear summation. Furthermore, we propose a model that computes prices as a function of time, thus permitting users, in particular consumers to adjust their demand trading off price and time of execution.