Informatica

In a fuzzy identity-based encryption (IBE) scheme, a user with the secret key for an identity ID is able to decrypt a ciphertext encrypted with another identity ID' if and only if ID and ID' are within a certain distance of each other as judged by some metric. Fuzzy IBE also allows to encrypt a document to all users that have a certain set of attributes. In 2005, Sahai and Waters first proposed the notion of fuzzy IBE and proved the security of their scheme under the selective-ID model. Currently, there is no fuzzy IBE scheme available that is fully CCA2 secure in the standard model. In this paper, we propose a new fuzzy IBE scheme which achieves IND-FID-CCA2 security in the standard model with a tight reduction. Moreover, the size of public parameters is independent of the number of attributes associated with an identity.

In this paper new semilogarithmic quantizer for Laplacian distribution is presented. It is simpler than classic A-law semilogarithmic quantizer since it has unit gain around zero. Also, it gives for 2.97 dB higher signal-to-quantization noise-ratio (SQNR) for referent variance in relation to A-law, and therefore it is more suitable for adaptation. Forward adaptation of this quantizer is done on frame-by-frame basis. In this way G.712 standard is satisfied with 7 bits/sample, which is not possible with classic A-law. Inside each frame subframes are formed and lossless encoder is applied on subframes. In that way, double adaptation is done: adaptation on variance within frames and adaptation on amplitude within subframes. Joined design of quantizer and lossless encoder is done, which gives better performances. As a result, standard G.712 is satisfied with only 6.43 bits/sample. Experimental results, obtained by applying this model on speech signal, are presented. It is shown that experimental and theoretical results are matched very well (difference is less than 1.5%). Models presented in this paper can be applied for speech signal and any other signal with Laplacian distribution.

The paper deals with the use of formant features in dynamic time warping based speech recognition. These features can be simply visualized and give a new insight into understanding the reasons of speech recognition errors. The formant feature extraction method, based on the singular prediction polynomials, has been applied in recognition of isolated words. However, the speech recognition performance depends on the order of singular prediction polynomials, whether symmetric or antisymmetric singular prediction polynomials are used for recognition and as well on the fact even or odd order of these polynomials is chosen. Also, it is important to know how informative separate formants are, how the speech recognition results depend on other parameters of the recognition system such as: analysis frame length, number of the formants used in recognition, frequency scale used for representation of formant features, and the preemphasis filter parameters. Properly choosing the processing parameters, it is possible to optimize the speech recognition performance.

In this paper, we propose a mutual authentication scheme using nonce variable instead of Mac address and accompanying with token updates to improve the functionality. Lee et al. (2005a) and Shi et al. (2006) proposed the site authentication schemes by using the generating random numbers. The site authentication can identify a personal computer using LAN card's Mac address, but the Mac address is easily detected through Address Resolution Protocol in the Open Systems Interconnection model. Therefore, we propose an improved securer and efficient nonce-based authentication scheme providing mutual authentication to resist the replay attack, man-in-the-middle attack and Mac address attack.

In the presented paper, some issues of the fundamental classical mechanics theory in the sense of Ising physics are introduced into the applied neural network area. The expansion of the neural networks theory is based primarily on introducing Hebb postulate into the mean field theory as an instrument of analysis of complex systems. Appropriate propositions and a theorem with proofs were proposed. In addition, some computational background is presented and discussed.

Software localization is one of important tasks to insure a successful computer user experience. The paper discusses how localization of the software dialog text can be accelerated and how to raise the quality of software product localization. We also discuss the main features and common structure of localizable software resources, their formats and preparation for localization. As a result, we suggest applying a modified formalism of attribute grammars to describe localizable resources, taking the graphical user interface as a basic grammar structure, localizable strings and their parts as terminal symbols, and using the attributes to add important metainformation and context to the resources. The main principles of creation of such attribute grammars are presented.

A Group-Oriented Cryptosystem (GOC) allows a sender to encrypt a message sent to a group of users so only the specified sets of users in that group can cooperatively decrypt the message. Recently, Li et al. pointed out unauthorized sets in the receiving group can recover the encrypted messages in Yang et al.'s GOC; and they further repaired this security flaw. However, the improved GOC contains inexact security analysis. Further, conversion of the scheme into a threshold cryptosystem results in inefficiency. This study enhances Li et al.'s GOC, both in that it achieves the requirements of GOC but also that it can be efficiently converted into a threshold cryptosystem. Under the decisional Diffie–Hellman problem assumption, the proposed scheme is demonstrated to be provably secure against chosen plaintext attacks.

This study presents developed algorithm for assessment and updating estimates of parameters in the mathematical models of non-stationary processes (for instance, system ageing model, dynamic system models and so on) with respect of prior information and new obtained observations. Proposed algorithm for updating estimates of random parameters is based on modified application of Bayesian approach (BA). Developed algorithm was applied for Ignalina NPP Unit 2 RBMK-1500 reactor's closure of the gas-gap between the pressure tubes and the graphite bore probabilistic analysis.

A proxy signature scheme enables an original signer to delegate its signing capability to a proxy signer and then the proxy signer can sign a message on behalf of the original signer. Recently, in order to eliminate the use of certificates in certified public key cryptography and the key-escrow problem in identity-based cryptography, the notion of certificateless public key cryptography was introduced. In this paper, we first present a security model for certificateless proxy signature schemes, and then propose an efficient construction based on bilinear pairings. The security of the proposed scheme can be proved to be equivalent to the computational Diffie–Hellman problem in the random oracle with a tight reduction.

To suitably complete an image without seams, block effects, and artifacts, a novel exemplar-based image completion model employing partial differential equation (PDE) is proposed. Firstly, the novel model determines the processing order of exemplar according to a composite function, which is the product of the colour property and structure property in exemplar. Then the exemplar along a geometric structure is processed prior to other parts of the image. Secondly, the most similar exemplar is found in the CIELAB colour space, and the size of it is adaptively determined by the local textured information. Thirdly, a Poisson equation is adopted to remove the seams, block effects, and artifacts in the image generated by the exemplar-based model. Finally, a bi-directional diffusion PDE is used to assist the completion of lathy linear structure. Experimental results demonstrate that the novel model can properly reconstruct the target region while preserving the geometric structure without inducing block effects, which leads to its better performance than the conventional exemplar-based image completion models.