From Known-Plaintext Security to Chosen-Plaintext Security

We present a new encryption mode for block ciphers. The mode is efficient and is secure against chosen-plaintext attack (CPA) already if the underlying symmetric cipher is secure against known-plaintext attack (KPA). We prove that known (and widely used) encryption modes as CBC mode and counter mode do not have this property. In particular, we prove that CBC mode using a KPA secure cipher is KPA secure, but need not be CPA secure, and we prove that counter mode using a KPA secure cipher need not be even KPA secure. The analysis is done in a concrete security framework

Model-based Speech Enhancement for Intelligibility Improvement in Binaural Hearing Aids

Speech intelligibility is often severely degraded among hearing impaired individuals in situations such as the cocktail party scenario. The performance of the current hearing aid technology has been observed to be limited in these scenarios. In this paper, we propose a binaural speech enhancement framework that takes into consideration the speech production model. The enhancement framework proposed here is based on the Kalman filter that allows us to take the speech production dynamics into account during the enhancement process. The usage of a Kalman filter requires the estimation of clean speech and noise short term predictor (STP) parameters, and the clean speech pitch parameters. In this work, a binaural codebook-based method is proposed for estimating the STP parameters, and a directional pitch estimator based on the harmonic model and maximum likelihood principle is used to estimate the pitch parameters. The proposed method for estimating the STP and pitch parameters jointly uses the information from left and right ears, leading to a more robust estimation of the filter parameters. Objective measures such as PESQ and STOI have been used to evaluate the enhancement framework in different acoustic scenarios representative of the cocktail party scenario. We have also conducted subjective listening tests on a set of nine normal hearing subjects, to evaluate the performance in terms of intelligibility and quality improvement. The listening tests show that the proposed algorithm, even with access to only a single channel noisy observation, significantly improves the overall speech quality, and the speech intelligibility by up to 15%.Comment: after revisio

Eco-Forecasting for Domestic Electricity Use

Over the past decade we have seen an increased awareness about domestic energy consumption and a growing focus on eco-feedback displays. In this paper we explore the concept of providing forecasts in such displays as a supplement to information about past usage. Our prototype, eForecast, extends the display of past electricity usage with forecasts about expected usage, electricity price, availability of wind power, and expected demand drops and peaks. Building on previous eco-feedback display research, our approach specifically enables people to use electricity at more opportune times – when it is cheap, green, or when there is an abundance of capacity. We evaluated eForecast in real world use in three domestic households for 22 weeks, where we explored potentials and limitations of forecasting for shifting electricity consumption. In this way, families were able to act in a more sustainable way – without necessarily reducing the amount of electricity consumed. Author Keywords Sustainability; forecasting; energy consumption; domesti