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{ "item_title" : "Foundations and Practice of Security", "item_author" : [" Esma Aïmeur", "Maryline Laurent", "Reda Yaich "], "item_description" : "This book constitutes the revised selected papers of the 14th International Symposium on Foundations and Practice of Security, FPS 2021, held in Paris, France, in December 2021.The 18 full papers and 9 short paper presented in this book were carefully reviewed and selected from 62 submissions. They cover a range of topics such as Analysis and Detection; Prevention and Efficiency; and Privacy by Design.Chapters A Quantile-based Watermarking Approach for Distortion Minimization, Choosing Wordlists for Password Guessing: An Adaptive Multi-Armed Bandit Approach and A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/108/146/3031081463_b.jpg", "price_data" : { "retail_price" : "64.99", "online_price" : "64.99", "our_price" : "64.99", "club_price" : "64.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Foundations and Practice of Security|Esma Aïmeur

Foundations and Practice of Security : 14th International Symposium, Fps 2021, Paris, France, December 7-10, 2021, Revised Selected Papers

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Overview

This book constitutes the revised selected papers of the 14th International Symposium on Foundations and Practice of Security, FPS 2021, held in Paris, France, in December 2021.

The 18 full papers and 9 short paper presented in this book were carefully reviewed and selected from 62 submissions. They cover a range of topics such as Analysis and Detection; Prevention and Efficiency; and Privacy by Design.

Chapters "A Quantile-based Watermarking Approach for Distortion Minimization", "Choosing Wordlists for Password Guessing: An Adaptive Multi-Armed Bandit Approach" and "A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This item is Non-Returnable

Details

  • ISBN-13: 9783031081460
  • ISBN-10: 3031081463
  • Publisher: Springer
  • Publish Date: June 2022
  • Dimensions: 9.21 x 6.14 x 0.88 inches
  • Shipping Weight: 1.33 pounds
  • Page Count: 416

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