title: ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð½Ð¾ÑÑÐ¸ Ð´Ð°Ð½Ð½ÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ°
titleType: Subtitle
title: Algorithms for ensuring k-anonymity of data
Creators: name: Ð Ð¾ÑÐ»ÑÐºÐ¾Ð²Ð°, ÐÐ½Ð½Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ
k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð½Ð¾ÑÑÑ
Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ñ
Ð±Ð¾Ð»ÑÑÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ
k-anonymity
anonymization
big data

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð½Ð¾ÑÑÐ¸ Ð´Ð°Ð½Ð½ÑÑÂ». Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ²ÐµÐ»Ð¸ÑÐµÐ½Ð¸Ðµ Ð±ÑÑÑÑÐ¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð° k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»Ñ Ð±Ð¾Ð»ÑÑÐ¾Ð³Ð¾ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° Ð°ÑÑÐ¸Ð±ÑÑÐ¾Ð². ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÐ¼ÑÐµ Ð´Ð»Ñ Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ.Â ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð° Ð½Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐ»ÑÑÑÐµÐ½Ð¸Ð¹ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð² Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°Ñ k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð´Ð°Ð½Ð½ÑÑ. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1. ÐÐ½Ð°Ð»Ð¸Ð· Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸. 2. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¿Ð¾ÑÐ¾Ð±Ð° Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ Ð±ÑÑÑÑÐ¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð²ÑÐ±ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸. 3. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ ÑÐ¿Ð¾ÑÐ¾Ð±Ð°. 4. Ð­ÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð¾Ðµ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿Ð°. Ð ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²Ð¸Ð¸ Ñ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½ÑÐ¼Ð¸ ÑÐµÐ»ÑÐ¼Ð¸ Ð¸ Ð·Ð°Ð´Ð°ÑÐ°Ð¼Ð¸ Ð±ÑÐ»Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð¼ÐµÑÐ¾Ð´Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸, Ð²ÐºÐ»ÑÑÐ°ÑÑÐ¸Ð¹ Ð¿. 1, Ð¿. 2 Ð¸Ð· ÑÐ¿Ð¸ÑÐºÐ° Ð·Ð°Ð´Ð°Ñ Ð²ÑÑÐµ, Ð¸ Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ¸Ð¹, Ð²ÐºÐ»ÑÑÐ°ÑÑÐ¸Ð¹ Ð¿. 3, Ð¿. 4. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÐÐÐ  Ð±ÑÐ» ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ k-Ð°Ð½Ð¾Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð±Ð¾Ð»ÑÑÐ¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° KGen Ð½Ð° ÑÐ·ÑÐºÐµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Java Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐ° jMetal.
description: The topic of the final qualifying work: Â«Algorithms for ensuring k-anonymity of dataÂ». The aim of the work is to increase the speed of the k-anonymization method for a large number of attributes. The subject of the study is the k-anonymization algorithms used to anonymize big data.Â This work is aimed at investigating the possibility of using improvements of the genetic algorithm in algorithms of k-anonymization of data. Tasks solved in the course of the study: 1. Analysis of k-anonymization algorithms. 2. Development of a method to improve the performance of the selected algorithm of k-anonymization. 3. Implementation of the developed method. 4. Experimental testing of the developed prototype. In accordance with the set goals and objectives, the following research methods were applied: theoretical analysis of k-anonymization methods, including paragraphs 1, paragraph 2 from the list of tasks above, and practical, including paragraphs 3, paragraph 4. As a result of the final qualifying work, a software prototype of k-anonymization of a large data set based on the KGen algorithm in the language Java programming using the jMetal framework.