We consider the problem of building robust fuzzy extractors, which allow two parties holding similar random variables W , W ′ to agree on a secret key R in the presence of an active adversary. Robust fuzzy extractors were defined by Dodis et al. in Crypto 2006 [6] to be noninteractive, i.e., only one message P , which can be modified by an unbounded adversary, can pass from one party to the oth...

When designing Natural Language Processing (NLP) applications that use Machine Learning (ML) techniques, feature extraction becomes a significant part of the development effort, whether developing a new application or attempting to reproduce results reported for existing NLP tasks. We present EDISON, a Java library of feature generation functions used in a suite of state-of-the-art NLP tools, b...

Domestic cooking is critical for release of particulate matter (PM) in indoor environments. This study tested low-cost sensors to assess PM from student studio flats different methods and establish the impact extractors.

In an imbalanced dataset, the positive and negative classes can be quite different in both size and distribution. This degrades the performance of many feature extraction methods and classifiers. This paper proposes a method for extracting minimum positive and maximum negative features (in terms of absolute value) for imbalanced binary classification. This paper develops two models to yield the...

We initiate a study of Maurer’s bounded storage model (JoC, 1992) in presence of transmission errors and perhaps other types of errors that cause different parties to have inconsistent views of the public random source. Such errors seem inevitable in any implementation of the model. All previous schemes and protocols in the model assume a perfectly consistent view of the public source from all ...

A Fuzzy Extractor (Dodis et al., Eurocrypt 2004) is a two-step protocol that turns a noisy secret into a uniformly distributed key R. To eliminate noise, the generation procedure takes as input an enrollment value ω and outputsR and a helper string P that enables further reproduction ofR from some close reading ω′. Boyen highlighted the need for reusable fuzzy extractors (CCS 2004) that remain ...

A fuzzy extractor (Dodis et al., Eurocrypt 2004) is a pair of procedures that turns a noisy secret into a uniformly distributed key R. To eliminate noise, the generation procedure takes as input an enrollment value ω and outputsR and a helper string P that enables further reproduction ofR from some close reading ω′. Boyen highlighted the need for reusable fuzzy extractors (CCS 2004) that remain...

The recent line of study on randomness extractors has been a great success, resulting in exciting new techniques, new connections, and breakthroughs to long standing open problems in the following five seemingly different topics: seeded non-malleable extractors, privacy amplification protocols with an active adversary, independent source extractors (and explicit Ramsey graphs), non-malleable in...

Establishing a strong link between the paper medium and the data represented on it is an interesting alternative to defeat unauthorized copy and content modification attempts. Many applications would benefit from it, such as show tickets, contracts, banknotes or medical prescripts. In this paper, we present a low cost solution that establishes such a link by combining digital signatures, physic...

Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the perfo...