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{ "item_title" : "Availability, Reliability, and Security in Information Systems", "item_author" : [" Francesco Buccafurri", "Andreas Holzinger", "Peter Kieseberg "], "item_description" : "This volume constitutes the refereed proceedings of the IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference on Availability, Reliability and Security in Information Systems, CD-ARES 2016, and the Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016, co-located with the International Conference on Availability, Reliability and Security, ARES 2016, held in Salzburg, Austria, in September 2016. The 13 revised full papers and 4 short papers presented were carefully reviewed and selected from 23 submissions. They are organized in the following topical sections: Web and semantics; diagnosis, prediction and machine learning; security and privacy; visualization and risk management; and privacy aware machine learning for health data science.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/31/945/506/3319455060_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Availability, Reliability, and Security in Information Systems|Francesco Buccafurri

Availability, Reliability, and Security in Information Systems : Ifip Wg 8.4, 8.9, Tc 5 International Cross-Domain Conference, CD-Ares 2016, and Worksh

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Overview

This volume constitutes the refereed proceedings of the IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference on Availability, Reliability and Security in Information Systems, CD-ARES 2016, and the Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016, co-located with the International Conference on Availability, Reliability and Security, ARES 2016, held in Salzburg, Austria, in September 2016. The 13 revised full papers and 4 short papers presented were carefully reviewed and selected from 23 submissions. They are organized in the following topical sections: Web and semantics; diagnosis, prediction and machine learning; security and privacy; visualization and risk management; and privacy aware machine learning for health data science.

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Details

  • ISBN-13: 9783319455068
  • ISBN-10: 3319455060
  • Publisher: Springer
  • Publish Date: August 2016
  • Dimensions: 9.21 x 6.14 x 0.59 inches
  • Shipping Weight: 0.87 pounds
  • Page Count: 267

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