Items related to Availability, Reliability, and Security in Information...

Availability, Reliability, and Security in Information Systems: IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference, CD-ARES 2016, and ... (Lecture Notes in Computer Science, 9817) - Softcover

 
9783319455068: Availability, Reliability, and Security in Information Systems: IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference, CD-ARES 2016, and ... (Lecture Notes in Computer Science, 9817)

Synopsis

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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From the Back Cover

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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