Informatica

Fuzzy identity based encryption (FIBE), proposed by Sahai and Waters, is a new kind of identity based encryption. It allows users with identity w can decrypt ciphertext for w' if and only if w is close enough to w'. Recently, Ren et al. proposed a new FIBE scheme and claimed it is fully CCA2 secure in the standard model with a tight reduction. However, in this paper we will show that their scheme is not correct. Furthermore, the key generation process of their scheme cannot resist the collusion attack, which is a basic security requirement for FIBE. At last, we propose a new fully secure FIBE scheme based on the Sahai–Waters FIBE scheme and prove its security by using the “dual system encryption” technique.

The notion of general backlash is introduced where instead of the straight lines determining the upward and downward parts of backlash characteristic general curves are considered. An analytic form of general backlash characteristic description is proposed, which is based on appropriate switching and internal functions. Consequently, this multi-valued mapping is represented by one difference equation. All the parameters in the equation describing this hard nonlinearity are separated; hence the general backlash identification can be solved as a quasi-linear problem using an iterative parameter estimation method with internal variable estimation. Also the identification of cascaded systems consisting of a general input backlash followed by a linear dynamic system is presented. Simulation studies of general backlash identification and that of cascaded systems with general input backlash are included.

In this paper we describe possible approaches how to store XML data, which is a key aspect for their further processing. One popular technique for managing XML data is to map the data to an existing database system, e.g., to the relational or object-relational database management system. We describe possible ways how to store XML data in relational databases, because relational systems are still widely used for various purposes, including XML data management. But XML data are trees, not tables, so the main focus of this article is oriented to native XML databases. We describe general properties of such kind of databases and, in particular, explain possible solutions on two experimental native XML database management systems – ExDB and CellStore. Both have been proposed, implemented and optimized in our research groups in recent years for experimental purposes.

A logistics system that involves a supplier who produces and delivers a single product and a buyer who receives and sells the product to the final customers was analyzed. A mathematical model was developed to describe the behavior of the system and to derive the optimal cycle length and order-up-to levels for the two parties. An analysis of the obtained results revealed that the methods were able to determine the optimal control parameters for each party in a short time frame. A coordination mechanism based on the optimal policies was ultimately proposed so that each party benefits more than if they use their own optimal control policy.

The emergence of the Semantic Web have revived the interest in knowledge engineering and ontologies. Different paradigms often share challenges and solutions, and can complement and mutually improve each other. This paper presents a simple and agile integration of ontologies and programming on a small scale, and in a down-to-Earth manner by incorporating the ontology paradigm into a mainstream programming environment. The approach is based on metaprogramming, which has been used to internalize the ontology modeling paradigm into the Clojure language. The resulting DSL, Magic Potion, is implemented in Cojure and blends ontology, functional, object-oriented and concurrent paradigms, which is suitable for general-purpose domain modeling, from technology enhanced learning to business.

Regarding the complexity of actual software systems, including web portals, it is becoming more and more difficult to develop software systems such that their real usage will satisfy their intended usage. To tackle this problem, we can compare the a priori assumptions about how the system should be used with the actual user behavior in order to decide how the system could be improved. For this aim, we propose to employ the same formalism to express the intended usage, the web portal model and the real usage extracted from system usage traces by data mining algorithms. Inspired from BioCham, we propose to use temporal logic and Kripke structure as such a common formalism.

This paper aims to extend fuzzy MULTIMOORA with linguistic reasoning and group decision-making (MULTIMOORA-FG). The new method consists of the three parts, namely the fuzzy Ratio System, the fuzzy Utopian Reference Point, and the fuzzy Full Multiplicative Form offering a robust comparison of alternatives against multiple objectives. In addition, MULTIMOORA-FG is designed to deal with triangular fuzzy numbers which, in turn, can resemble linguistic variables. MULTIMOORA-FG is a proper instrument for linguistic reasoning under fuzzy environment. In our study an application of personnel selection illustrates the group decision-making procedure according to MULTIMOORA-FG. Given the uncertainties peculiar of personnel selection, the application of multi-objective decision making (MODM) is required in this area. Fuzzy MULTIMOORA enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform a more robust personnel selection. The committee decided to consider eight qualitative characteristics expressed in linguistic variables. A numerical example exhibited possibilities for improvement of human resources management or any other business decision-making by applying MULTIMOORA-FG.

User anonymity is very important security technique in distributed computing environments that an illegal entity cannot determine any information concerning the user's identity. In 2006, Kumar–Rajendra proposed a Secure Identification and Key agreement protocol with user Anonymity (SIKA). This paper demonstrates the vulnerability of the SIKA protocol and then presents an improvement to repair the security flaws of the SIKA protocol.

In some cases of using multi-criteria decision making methods for solving real-world problems ratings of alternatives cannot be determined precisely, and that is why they are expressed in the form of intervals. Therefore, the aim of this paper is to extend the MOORA method for solving decision making problems with interval data. By extending the ratio system part of MOORA method, an algorithm to determine the most preferable alternative among all possible alternatives, when performance ratings are given as intervals, is presented. Finally, an example is shown to highlight the proposed procedure, at the end of this paper.

In this paper, a piecewise uniform quantizer for input samples with discrete amplitudes for Laplacian source is designed and analyzed, and its forward adaptation is done. This type of quantizers is very often used in practice for the purpose of compression and coding of already quantized signals. It is shown that the design and the adaptation of quantizers for discrete input samples are different from the design and the adaptation of quantizers for continual input samples. A weighting function for PSQNR (peak signal-to-quantization noise ratio), which is obtained based on probability density function of variance of standard test images is introduced. Experiments are done, applying these quantizers for compression of grayscale images. Experimental results are very well matched to the theoretical results, proving the theory. Adaptive piecewise uniform quantizer designed for discrete input samples gives for 9 to 20 dB higher PSQNR compared to the fixed piecewise uniform quantizer designed for discrete input samples. Also it is shown that the adaptive piecewise uniform quantizer designed for discrete input samples gives higher PSQNR for 1.46 to 3.45 dB compared the adaptive piecewise uniform quantizer designed for continual input samples, which proves that the discrete model is more appropriate for image quantization than continual model.