1,720,968 research outputs found
Publicly Verifiable Zero Knowledge from (Collapsing) Blockchains
No full textPublicly Verifiable Zero-Knowledge proofs are known to exist only from setup assumptions such as a trusted common reference string or a random oracle. Unfortunately, the former requires a trusted party while the latter does not exist. Blockchains are distributed systems that already exist and provide certain security properties (under some honest majority assumption), hence, a natural recent research direction has been to use a blockchain as an alternative setup assumption. In TCC 2017 Goyal and Goyal proposed a construction of a publicly verifiable zero-knowledge (pvZK) proof system for some proof-of-stake blockchains. The zero-knowledge property of their construction however relies on some additional and not fully specified assumptions about the current and future behavior of honest blockchain players. In this paper we provide several contributions. First, we show that when using a blockchain to design a provably secure protocol, it is dangerous to rely on demanding additional requirements on behaviors of the blockchain players. We do so by showing an “attack of the clones” whereby a malicious verifier can use a smart contract to slyly (not through bribing) clone capabilities of honest stakeholders and use those to invalidate the zero-knowledge property of the proof system by Goyal and Goyal. Second, we propose a new publicly verifiable zero-knowledge proof system that relies on non-interactive commitments and on an assumption on the min-entropy of some blocks appearing on the blockchain. Third, motivated by the fact that blockchains are a recent innovation and their resilience in the long run is still controversial, we introduce the concept of collapsing blockchain, and we prove that the zero-knowledge property of our scheme holds even if the blockchain eventually becomes insecure and all blockchain players eventually become dishonest
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
Targeted Advertising That Protects the Privacy of Social Networks Users
No full textNowadays, the massive use of social media provides useful unstructured knowledge that can be used to enhance the efficacy of online brand marketing campaigns. The unstructured nature of social media content and the relevance of the contextual dimension, like time, stress the requirements for extracting users' interests during the timeline. However, user profiling could have some unpleasant consequences for users' privacy, thus raising the need to define methodologies capable of avoiding privacy leaks despite the exploitation of interactions over social media. This paper presents both an intelligent method of profiling social media users and a privacy protection technique that is designed to match users' profiles and advertisements, and which could be used by advertising agencies. The proposed method performssemantic data analysis for extracting representations of the contents of messages exchanged by users over social media (e.g.,tweets), by exploiting rough set theory. In this way, users' interestis obtained by mining their daily online activity. The proposed framework investigates two-party scenarios, i.e., scenarios composed of a social network owner and an advertising agency willing to promote its client's products through the social network. This paper presents three privacy-preserving matching protocols which enable targeted advertising without compromising the privacy of either the users or the advertisers. Starting from a recently proposed advertisement matching protocol, a private layer was added to ensure that any sensitive information of either party is kept private. In this way, the social network and the advertiser could benefit from a system which allows them to run a matching protocol with the guarantee that sensitive user data (for the social network) and business information (for the advertiser) will not be disclosed. The first two protocols require interaction between the Advertiser and the Online Social Network, while the third one outsources to a semi-trusted service provider some of the computation done during the execution of the advertisement matching. The experimental results are also presented to illustrate the proposed system's good performance to discover potentially interested users given an advertisement as input
Managing Constraints in Role Based Access Control
Full text linkRole-based access control (RBAC) is the most popular access control model currently adopted in several contexts to define security management. Constraints play a crucial role since they can drive the selection of the best representation of the organization's security policies when migrating towards an RBAC system. In this paper, we examine different types of constraints addressing both theoretical aspects and practical considerations. On one side, we define the constrained role mining problem for each constraint type, showing its complexity. On the other hand, we present efficient heuristics adapted to each class of constraints, all derived from the specialization of a general approach for role mining. We show that our techniques improve over previous proposals, offering a complete set of experimentations obtained after the application of the heuristics to standard real-world datasets
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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