1,720,960 research outputs found
Privacy preserving cloud computing through piecewise approximation of multivariate functions
No full textIn cloud computing, computation is demanded to several cloud computing servers and each of them can have access to different data sets. Such data and also the derived computation results could not be publicly shared among the clouds involved for privacy reasons. Secure Multi-Party Computation (SMPC) protocols could be used to protect private data during computation. The search for efficient universal computing architectures is an active research topic in SMPC. By extending a previous protocol for the piece-wise linear approximation of a generic one-dimensional function, a new SMPC protocol for the approximation of n-dimensional functions f(x1,..., xn) can be developed. In the case of two inputs, a quad-tree decomposition is used to decompose the function domain into subsets wherein a constant or a bilinear approximation is used. This solution can be easily extended to the approximation of n-variate functions. Two different implementations are considered: the first one relies completely on Garbled Circuits (GC), while the second one exploits a hybrid construction where GC and Homomorphic Encryption (HE) are used together. As it is shown in the present paper, the best choice between the two approaches depends on the specific settings with the hybrid solution being preferable for inputs characterized by a large bit-length
Secure Evaluation of Private Functions through Piecewise Linear Approximation
No full textWhile Secure Multy-Party Computation is a well known solution for cooperative function evaluation on private inputs, few solutions exist that also permit to protect the to-be-evaluated function. In this paper, we propose a solution, based on Garbled Circuit (GC) theory, to provide Secure Function Evaluation of semi-Private Functions through Piecewise Linear Approximation (PLA). We show how to approximate a generic function through a PLA chosen in a set of functions that can be implemented with the same Boolean circuit. The function is protected by hiding the coefficients of the chosen PLA. The class of approximating functions is defined in such a way to allow an efficient implementation by means of GC's. Together with the security provided by Garbled Circuits theory, the security of the protocol is ensured by the very large number of approximating functions belonging to the PLA's set. The paper ends with an investigation of the trade-off between approximation accuracy and protocol settings
General function evaluation in a STPC setting via piecewise linear approximation
Full text linkWhile in theory any computable functions can be evaluated in a Secure Two Party Computation (STPC) framework, practical applications are often limited for complexity reasons and by the kind of operations that the available cryptographic tools permit. In this paper we propose an algorithm that, given a function f() and an interval belonging to its domain, produces a piecewise linear approximation f() that can be easily implemented in a STPC setting. Two different implementations are proposed: the first one relies completely on Garbled Circuit (GC) theory, while the second one exploits a hybrid construction where GC and Homomorphic Encryption (HE) are used together. We show that from a communication complexity perspective the full-GC implementation is preferable when the input and output variables are represented with a small number of bits, otherwise the hybrid solution is preferable
An efficient protocol for private iris-code matching by means of garbled circuits
No full textBiometric-based access control is receiving increasing attention due to its security and ease-of-use. However, concerns are often raised regarding the protection of the privacy of enrolled users. Signal processing in the encrypted domain has been proposed as a viable solution to protect biometric templates and the privacy of the users. In particular, several solutions have been proposed to protect the privacy of the biometric probe during the authentication process. In this paper we focus on privacy-preserving iris-based authentication. The main innovations compared to the prior art include: i) an iris masking technique that simplifies the operations on the encrypted data without sacrificing the recognition rate; ii) the adoption of a matching protocol based only on garbled circuits which offers longer term security over existing solutions based on homomorphic encryption or hybrid techniques. The computational and communication complexity of the on-line phase of the proposed protocol is extremely low, thus opening the way to its exploitation in practical applications
Semba: Secure multi-biometric authentication
Full text linkBiometrics security is a dynamic research area spurred by the need to protect personal traits from threats like theft, non-authorised distribution, reuse and so on. A widely investigated solution to such threats consists of processing the biometric signals under encryption, in order to avoid any leakage of information towards non-authorised parties. In this study, the authors propose to leverage on the superior performance of multimodal biometric recognition to improve the efficiency of a biometric-based authentication protocol operating on encrypted data under the malicious security model. In the proposed protocol, authentication relies on both facial and iris biometrics, whose representation accuracy is specifically tailored to the trade-off between recognition accuracy and efficiency. From a cryptographic point of view, the protocol relies on Damgård et al. SPDZ. Experimental results show that the multimodal protocol is faster than corresponding unimodal protocols achieving the same accuracy
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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