优化算法在所有权保留数据挖掘中的应用

Muhammad KAMRAN; Ehsan Ullah MUNIR

doi:10.1631/FITEE.1601479

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优化算法在所有权保留数据挖掘中的应用

常规文章 | Updated：2022-05-19

- 优化算法在所有权保留数据挖掘中的应用
- On the role of optimization algorithms in ownership-preserving data mining
- 信息与电子工程前沿（英文） 2018年19卷第2期页码：151-164
- Affiliations：
  
  Department of Computer Science, COMSATS Institute of Information Technology, Wah Cantt 47010, Pakistan
- Author bio：
  
  Muhammad KAMRAN, E-mail: muhammad.kamran@ciitwah.edu.pk
  [ "Ehsan Ullah MUNIR, E-mail: ehsanmunir@comsats.edu.pk" ]
- Funds：
- DOI：10.1631/FITEE.1601479
  中图分类号： TP309
- 收稿：2016-08-17，
  
  修回：2018-;2-15，
  
  纸质出版：2018-02
- Accepted：
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Muhammad KAMRAN, Ehsan Ullah MUNIR. 优化算法在所有权保留数据挖掘中的应用[J]. 信息与电子工程前沿（英文）, 2018,19(2):151-164.

Muhammad KAMRAN, Ehsan Ullah MUNIR. On the role of optimization algorithms in ownership-preserving data mining[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(2): 151-164.
Muhammad KAMRAN, Ehsan Ullah MUNIR. 优化算法在所有权保留数据挖掘中的应用[J]. 信息与电子工程前沿（英文）, 2018,19(2):151-164. DOI： 10.1631/FITEE.1601479.

Muhammad KAMRAN, Ehsan Ullah MUNIR. On the role of optimization algorithms in ownership-preserving data mining[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(2): 151-164. DOI： 10.1631/FITEE.1601479.

摘要

从敏感数据中提取知识往往需要协同工作。统计数据库根据这些敏感数据生成，并由各利益相关方共享。在此情况下，共享数据的所有权保护变得尤为重要。水印技术正逐渐成为一种推行数字数据格式所有权的有效工具，但该技术也可能导致数据失真。因此，从具有水印的数据中提取的知识可能不准确。数据失真程度由可用性约束条件来控制，这反过来又限制了可用于添加水印的带宽。尽管大带宽能保证鲁棒性，但可能降低数据质量。该问题可以通过在可用性约束条件下优化可用带宽来解决。如今，优化技术--尤其是生物启发式技术--已成为解决该类问题的首选。本文分析了多种优化方案及其可行性，用于优化添加水印的最大可用带宽，并期望达到以下两个目标：（1）保持数据中存储的知识不变；（2）在可用性约束条件下使可用带宽最大化，以取得最佳鲁棒性。第一个目标利用一个可用性约束模型实现，该模型能确保知识不会因嵌入水印而受到损害。第二个目标通过找到满足第一个目标的可用性约束条件下最大带宽实现。采用不同指标对多种优化方案性能进行了评估。

Abstract

Knowledge extraction from sensitive data often needs collaborative work. Statistical databases are generated from such data and shared among various stakeholders. In this context

the ownership protection of shared data becomes important. Watermarking is emerging to be a very effective tool for imposing ownership rights on various digital data formats. Watermarking of such datasets may bring distortions in the data. Consequently

the extracted knowledge may be inaccurate. These distortions are controlled by the usability constraints

which in turn limit the available bandwidth for watermarking. Large bandwidth ensures robustness; however

it may degrade the quality of the data. Such a situation can be resolved by optimizing the available bandwidth subject to the usability constraints. Optimization techniques

particularly bioinspired techniques

have become a preferred choice for solving such issues during the past few years. In this paper

we investigate the usability of various optimization schemes for identifying the maximum available bandwidth to achieve two objectives: (1) preserving the knowledge stored in the data; (2) maximizing the available bandwidth subject to the usability constraints to achieve maximum robustness. The first objective is achieved with a usability constraint model

which ensures that the knowledge is not compromised as a result of watermark embedding. The second objective is achieved by finding the maximum bandwidth subject to the usability constraints specified in the first objective. The performance of optimization schemes is evaluated using different metrics.

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references

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