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Many different quantitative assessment models have been proposed to measure and report the usability of a general software product for various business and design purposes. However, there are several problems coupled with existing models that consequently bias and affect the process and results of the usability assessment. Moreover, they do not aid their usage by analysts who are not experienced in the filed of usability. Therefore, an integrated, accurate, consolidated and simple usability assessment model is required, to provide an entire construct of usability for general software products. In this paper, we proposed an Integrated Quantitative Assessment Model for Usability Engineering (IQAMUE) for measuring and reporting usability for general software products. The contribution of the IQAMUE has been done at several points: (1) The investigation into existing models that represents usability factors, either by standard bodies or by well-known researches in the field of usability. As a result, we have proposed an improved comprehensive model, which integrates potential and general usability factors, and measure their related metrics in a standard way (2) We have proposed an adjustable sample size estimation model for usability assessment, which enhances the estimation process, by using historical data to gain an initial idea of the software product, and on present data to predict the complexity of the software product (3) For the applicability purpose of the proposed model, we have conducted an empirical case study for a local e-mail system (Eudora V7) to examine and practice the proposed model

Usability assessment plays a fundamental role in discovering usability problems and the determination of the level of usability for a given software product. One crucial aspect in every usability assessment is the estimation of the sample size desired for a software product. Once we start estimating the sample size needed for a usability assessment, a baffling question comes in mind: "how many users are enough for a given software product?". To the best of our knowledge, the majority of existing models estimates the sample size needed for a usability assessment, based on historical data. A better estimation should be based on both historical data, which provide an initial idea from previous software products and based on present data, which provide a practical idea for a given software product. Therefore, in this paper we have proposed an adjustable sample size estimation model for usability assessment, which enhances the estimation process by using two factors: Alpha factor (α), which estimates the problem discovery rate (λ_α) from historical data and the Beta factor (β), which estimates the problem discovery rate (λ_β) by using the complexity of the software product. λ_β is taken as vertical and domain wise for a given software product, to adjust the alpha factor appropriately to give the desired confidence level in the results. An illustrative case study has been provided at the end of the paper

In 2005, Lee suggested a password scheme for three participants without trusted server. Lee claimed that the scheme can withstand different attacks and give the perfect secrecy. In this paper, the authors demonstrate what the Lee scheme undergoes from the imitation attack. Simultaneously, the authors suggest an enhanced algorithm to resist the mentioned attacks.