A fast algorithm for hiding high utility sequential patterns

Chunkai Zhang; Yiwen Zu; Junli Nie; Linzi Du; Jingqi Du; Siyuan Hong; Wenping Wu

doi:10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

A fast algorithm for hiding high utility sequential patterns

Chunkai Zhang
, Yiwen Zu
, Junli Nie
, Linzi Du
, Jingqi Du
, Siyuan Hong
, Wenping Wu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

High utility sequential patterns (HUSPs) are common patterns that can be discovered from the data collected in many domains (e.g. retail, bioinformatics, mobile commerce). To extract these patterns, high utility sequential pattern mining (HUSPM) has been proposed in recent decade. Although the HUSPM algorithms provide us a special perspective to analyze the knowledge behind the collected data, it also arises the risk of the privacy leakage and underlying security issues. This leads to the emergence of high utility sequential pattern hiding (HUSPH) whose purpose is to hide all HUSPs in the sequence database under a specified threshold. Around this topic, many algorithms were proposed. However, the existing algorithms are very time-consuming, which makes them unable to process the real massive data quickly. In this paper, we propose an efficient algorithm named FH-HUSP (fast algorithm for hiding high utility sequential patterns) for HUSPH. Substantial experimental results show that the proposed algorithm can hide all high utility sequential patterns quickly under the specific minimum utility with relatively small modifications.

Original language	English
Title of host publication	Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1316-1322
Number of pages	7
ISBN (Electronic)	9781728143286
DOIs	https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189
State	Published - Dec 2019
Externally published	Yes
Event	17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019 - Xiamen, China Duration: 16 Dec 2019 → 18 Dec 2019

Publication series

Name	Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019

Conference

Conference	17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
Country/Territory	China
City	Xiamen
Period	16/12/19 → 18/12/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Data mining
High utility sequential pattern
Privacy preserving data mining

Access to Document

10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

Cite this

Zhang, C., Zu, Y., Nie, J., Du, L., Du, J., Hong, S., & Wu, W. (2019). A fast algorithm for hiding high utility sequential patterns. In Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019 (pp. 1316-1322). Article 9047364 (Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

Zhang, Chunkai ; Zu, Yiwen ; Nie, Junli et al. / A fast algorithm for hiding high utility sequential patterns. Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1316-1322 (Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019).

@inproceedings{e1bf04c9743549778ba05def84e55106,

title = "A fast algorithm for hiding high utility sequential patterns",

abstract = "High utility sequential patterns (HUSPs) are common patterns that can be discovered from the data collected in many domains (e.g. retail, bioinformatics, mobile commerce). To extract these patterns, high utility sequential pattern mining (HUSPM) has been proposed in recent decade. Although the HUSPM algorithms provide us a special perspective to analyze the knowledge behind the collected data, it also arises the risk of the privacy leakage and underlying security issues. This leads to the emergence of high utility sequential pattern hiding (HUSPH) whose purpose is to hide all HUSPs in the sequence database under a specified threshold. Around this topic, many algorithms were proposed. However, the existing algorithms are very time-consuming, which makes them unable to process the real massive data quickly. In this paper, we propose an efficient algorithm named FH-HUSP (fast algorithm for hiding high utility sequential patterns) for HUSPH. Substantial experimental results show that the proposed algorithm can hide all high utility sequential patterns quickly under the specific minimum utility with relatively small modifications.",

keywords = "Data mining, High utility sequential pattern, Privacy preserving data mining",

author = "Chunkai Zhang and Yiwen Zu and Junli Nie and Linzi Du and Jingqi Du and Siyuan Hong and Wenping Wu",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019 ; Conference date: 16-12-2019 Through 18-12-2019",

year = "2019",

month = dec,

doi = "10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189",

language = "英语",

series = "Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1316--1322",

booktitle = "Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019",

address = "美国",

}

Zhang, C, Zu, Y, Nie, J, Du, L, Du, J, Hong, S & Wu, W 2019, A fast algorithm for hiding high utility sequential patterns. in Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019., 9047364, Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1316-1322, 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019, Xiamen, China, 16/12/19. https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

A fast algorithm for hiding high utility sequential patterns. / Zhang, Chunkai; Zu, Yiwen; Nie, Junli et al.
Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1316-1322 9047364 (Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A fast algorithm for hiding high utility sequential patterns

AU - Zhang, Chunkai

AU - Zu, Yiwen

AU - Nie, Junli

AU - Du, Linzi

AU - Du, Jingqi

AU - Hong, Siyuan

AU - Wu, Wenping

PY - 2019/12

Y1 - 2019/12

N2 - High utility sequential patterns (HUSPs) are common patterns that can be discovered from the data collected in many domains (e.g. retail, bioinformatics, mobile commerce). To extract these patterns, high utility sequential pattern mining (HUSPM) has been proposed in recent decade. Although the HUSPM algorithms provide us a special perspective to analyze the knowledge behind the collected data, it also arises the risk of the privacy leakage and underlying security issues. This leads to the emergence of high utility sequential pattern hiding (HUSPH) whose purpose is to hide all HUSPs in the sequence database under a specified threshold. Around this topic, many algorithms were proposed. However, the existing algorithms are very time-consuming, which makes them unable to process the real massive data quickly. In this paper, we propose an efficient algorithm named FH-HUSP (fast algorithm for hiding high utility sequential patterns) for HUSPH. Substantial experimental results show that the proposed algorithm can hide all high utility sequential patterns quickly under the specific minimum utility with relatively small modifications.

AB - High utility sequential patterns (HUSPs) are common patterns that can be discovered from the data collected in many domains (e.g. retail, bioinformatics, mobile commerce). To extract these patterns, high utility sequential pattern mining (HUSPM) has been proposed in recent decade. Although the HUSPM algorithms provide us a special perspective to analyze the knowledge behind the collected data, it also arises the risk of the privacy leakage and underlying security issues. This leads to the emergence of high utility sequential pattern hiding (HUSPH) whose purpose is to hide all HUSPs in the sequence database under a specified threshold. Around this topic, many algorithms were proposed. However, the existing algorithms are very time-consuming, which makes them unable to process the real massive data quickly. In this paper, we propose an efficient algorithm named FH-HUSP (fast algorithm for hiding high utility sequential patterns) for HUSPH. Substantial experimental results show that the proposed algorithm can hide all high utility sequential patterns quickly under the specific minimum utility with relatively small modifications.

KW - Data mining

KW - High utility sequential pattern

KW - Privacy preserving data mining

UR - https://www.scopus.com/pages/publications/85085484748

U2 - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

DO - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

M3 - 会议稿件

AN - SCOPUS:85085484748

T3 - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019

SP - 1316

EP - 1322

BT - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019

Y2 - 16 December 2019 through 18 December 2019

ER -

Zhang C, Zu Y, Nie J, Du L, Du J, Hong S et al. A fast algorithm for hiding high utility sequential patterns. In Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1316-1322. 9047364. (Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019). doi: 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00189

A fast algorithm for hiding high utility sequential patterns

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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