Download Data Security and Security Data: 27th British National by Ken Barker (auth.), Lachlan M. MacKinnon (eds.) PDF

By Ken Barker (auth.), Lachlan M. MacKinnon (eds.)

This publication constitutes the completely refereed post-conference complaints of the twenty seventh British nationwide convention on Databases, BNCOD 27, held in Dundee, united kingdom, in June 2010. the ten revised complete papers and six brief papers, offered including three invited papers, 1 most sensible paper of the linked occasion on instructing, studying and overview of Databases (TLAD), and a couple of PhD discussion board top papers have been rigorously reviewed and chosen from forty two submissions. precise concentration of the convention has been "Data protection and safeguard info" and so the papers conceal a variety of issues corresponding to information safeguard, privateness and belief, safety information, info integration and interoperability, facts administration for ubiquitous and cellular computing, information mining and data extraction, information modelling and architectures, information provenance, dataspaces, information streaming, databases and the grid, dispensed details platforms, digital trade, firm structures, heterogeneous databases, commercial functions, infrastructures and structures, intermittently hooked up information, dossier entry tools and index constructions, handling legacy info, new functions and approaches, parallel and disbursed databases, peer-to-peer information administration, functionality modelling of ubiquitous facts use, own facts administration, question and manipulation languages, question processing and optimisation, medical functions, semantic net and ontologies, semi-structured facts, metadata and xml, consumer interfaces and information visualisation, net information administration and deep net, net providers, and workflow aid systems.

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Additional info for Data Security and Security Data: 27th British National Conference on Databases, BNCOD 27, Dundee, UK, June 29 - July 1, 2010. Revised Selected Papers

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Persons, households, or companies). Respectively, a microfile is a set of microdata reduced to one file that consists of attributive records describing each respondent. Statistical disclosure control (SDC) methods aim at receiving new, protected microdata basing on the original ones. But, such a procedure should meet following conditions [7, p. 399]: - Disclosure risk is low or at least adequate to protected information importance. - Both original and protected data, when analyzed, yield close, or even equal results.

Our empirical evidence strongly suggests that for uniform data distribution, a simple k-d tree search will yield an expected running time of O(k log(n)) for exact search of the k nearest neighbors. For each analysis, we start from the running times of Algorithms 1 and 2 and use the appropriate form of Q(k, n). The analyses simplify to the given forms under the natural assumption that n k. In both cases, Algorithm 2 gives a speedup of O(K ∗ ) over Algorithm 1. This speedup is conserved over more costly k-nn implementations, as long as Q(k, n) is polynomial in k and n.

The first is the na¨ıve algorithm, which is presented for comparison purposes. The second incorporates a known optimization to provide clear benefits for some data mining applications. We provide explanation and analysis of these benefits. In Section 4, we show how this optimization does not provide the same benefits for locally linear regression problems, but additional techniques can be applied to achieve the same speedup. In Section 5, we consider the case of environments without a priori knowledge of an upper bound on k.

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