Association Rule Hiding for Data Mining

Association Rule Hiding for Data Mining

Author: Aris Gkoulalas-Divanis

Publisher: Springer Science & Business Media

Published: 2010-05-17

Total Pages: 159

ISBN-13: 1441965696

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Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the problem of "hiding" sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.


Book Synopsis Association Rule Hiding for Data Mining by : Aris Gkoulalas-Divanis

Download or read book Association Rule Hiding for Data Mining written by Aris Gkoulalas-Divanis and published by Springer Science & Business Media. This book was released on 2010-05-17 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the problem of "hiding" sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.

Study of Association Rule Mining and Different Hiding Techniques

Study of Association Rule Mining and Different Hiding Techniques

Author:

Publisher:

Published:

Total Pages:

ISBN-13:

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Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. In this paper, we first focused on APRIORI algorithm, a popular data mining technique and compared the performances of a linked list based implementation as a basis and a tries-based implementation on it for mining frequent item sequences in a transactional database. We examined the data structure, implementation and algorithmic features mainly focusing on those that also arise in frequent item set mining. This algorithm has given us new capabilities to identify associations in large data sets. But a key problem, and still not sufficiently investigated, is the need to balance the confidentiality of the disclosed data with the legitimate needs of the data users. One rule is characterized as sensitive if its disclosure risk is above a certain privacy threshold. Sometimes, sensitive rules should not be disclosed to the public, since among other things, they may be used for inferring sensitive data, or they may provide business competitors with an advantage. So, next we worked with some association rule hiding algorithms and examined their performances in order to analyze their time complexity and the impact that they have in the original database. We worked on two different side effects - one was the number of new rules generated during the hiding process and the other one was the number of non-sensitive rules lost during the process.


Book Synopsis Study of Association Rule Mining and Different Hiding Techniques by :

Download or read book Study of Association Rule Mining and Different Hiding Techniques written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. In this paper, we first focused on APRIORI algorithm, a popular data mining technique and compared the performances of a linked list based implementation as a basis and a tries-based implementation on it for mining frequent item sequences in a transactional database. We examined the data structure, implementation and algorithmic features mainly focusing on those that also arise in frequent item set mining. This algorithm has given us new capabilities to identify associations in large data sets. But a key problem, and still not sufficiently investigated, is the need to balance the confidentiality of the disclosed data with the legitimate needs of the data users. One rule is characterized as sensitive if its disclosure risk is above a certain privacy threshold. Sometimes, sensitive rules should not be disclosed to the public, since among other things, they may be used for inferring sensitive data, or they may provide business competitors with an advantage. So, next we worked with some association rule hiding algorithms and examined their performances in order to analyze their time complexity and the impact that they have in the original database. We worked on two different side effects - one was the number of new rules generated during the hiding process and the other one was the number of non-sensitive rules lost during the process.

Research Anthology on Privatizing and Securing Data

Research Anthology on Privatizing and Securing Data

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2021-04-23

Total Pages: 2188

ISBN-13: 1799889556

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With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.


Book Synopsis Research Anthology on Privatizing and Securing Data by : Management Association, Information Resources

Download or read book Research Anthology on Privatizing and Securing Data written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-04-23 with total page 2188 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.

Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection

Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection

Author: Koh, Yun Sing

Publisher: IGI Global

Published: 2009-08-31

Total Pages: 320

ISBN-13: 1605667552

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"This book provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining"--Provided by publisher.


Book Synopsis Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection by : Koh, Yun Sing

Download or read book Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection written by Koh, Yun Sing and published by IGI Global. This book was released on 2009-08-31 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining"--Provided by publisher.

Association Rule Mining

Association Rule Mining

Author: Chengqi Zhang

Publisher: Springer

Published: 2003-08-01

Total Pages: 247

ISBN-13: 3540460276

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Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.


Book Synopsis Association Rule Mining by : Chengqi Zhang

Download or read book Association Rule Mining written by Chengqi Zhang and published by Springer. This book was released on 2003-08-01 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

Advances in Data Mining. Applications and Theoretical Aspects

Advances in Data Mining. Applications and Theoretical Aspects

Author: Petra Perner

Publisher: Springer

Published: 2016-06-27

Total Pages: 456

ISBN-13: 3319415611

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This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine, and in process control, industry, and society.


Book Synopsis Advances in Data Mining. Applications and Theoretical Aspects by : Petra Perner

Download or read book Advances in Data Mining. Applications and Theoretical Aspects written by Petra Perner and published by Springer. This book was released on 2016-06-27 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine, and in process control, industry, and society.

Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction

Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction

Author: Zhao, Yanchang

Publisher: IGI Global

Published: 2009-05-31

Total Pages: 394

ISBN-13: 1605664057

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Provides a systematic collection on post-mining, summarization and presentation of association rules, and new forms of association rules.


Book Synopsis Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction by : Zhao, Yanchang

Download or read book Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction written by Zhao, Yanchang and published by IGI Global. This book was released on 2009-05-31 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a systematic collection on post-mining, summarization and presentation of association rules, and new forms of association rules.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Author: Honghua Dai

Publisher: Springer Science & Business Media

Published: 2004-05-11

Total Pages: 731

ISBN-13: 354022064X

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This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.


Book Synopsis Advances in Knowledge Discovery and Data Mining by : Honghua Dai

Download or read book Advances in Knowledge Discovery and Data Mining written by Honghua Dai and published by Springer Science & Business Media. This book was released on 2004-05-11 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.

Designing a Multi Level Support Based Association Mining Algorithm

Designing a Multi Level Support Based Association Mining Algorithm

Author: Shanmuganathan Vasanthapriyan

Publisher: Lulu.com

Published: 2014-09-29

Total Pages: 93

ISBN-13: 1312559519

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Finding of hidden and previously unknown information in large collection of data is the process of data mining. Mining association rules is a very important model in data mining. Using association rules different type of regularities and patterns can be identified. The main approach of association rules is the market basket analysis which exposes relationships between the items customers are regularly buying. In most of the previous approaches of finding association rules a single minimum support threshold value is used for all the items or itemsets. But all the items in an itemset do not behave in the same way where some appear very frequently and some appear very rarely. Therefore the support requirements should vary with different items. Here we proposed new algorithm and was tested using different data sets to prove the advantages. The analysis showed that the proposed algorithm is easy and efficient and it saves time by focusing only on necessary associations comparing to existing algorithms.


Book Synopsis Designing a Multi Level Support Based Association Mining Algorithm by : Shanmuganathan Vasanthapriyan

Download or read book Designing a Multi Level Support Based Association Mining Algorithm written by Shanmuganathan Vasanthapriyan and published by Lulu.com. This book was released on 2014-09-29 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding of hidden and previously unknown information in large collection of data is the process of data mining. Mining association rules is a very important model in data mining. Using association rules different type of regularities and patterns can be identified. The main approach of association rules is the market basket analysis which exposes relationships between the items customers are regularly buying. In most of the previous approaches of finding association rules a single minimum support threshold value is used for all the items or itemsets. But all the items in an itemset do not behave in the same way where some appear very frequently and some appear very rarely. Therefore the support requirements should vary with different items. Here we proposed new algorithm and was tested using different data sets to prove the advantages. The analysis showed that the proposed algorithm is easy and efficient and it saves time by focusing only on necessary associations comparing to existing algorithms.

Privacy-Preserving Data Mining

Privacy-Preserving Data Mining

Author: Charu C. Aggarwal

Publisher: Springer Science & Business Media

Published: 2008-06-10

Total Pages: 524

ISBN-13: 0387709924

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Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.


Book Synopsis Privacy-Preserving Data Mining by : Charu C. Aggarwal

Download or read book Privacy-Preserving Data Mining written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2008-06-10 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.