Process mining and security: Visualization in database intrusion detection

Viet Huynh; An N T Le

doi:10.1007/978-3-642-30428-6_7

Process mining and security: Visualization in database intrusion detection

Viet Huynh, An N T Le

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

5 Citations (Scopus)

Abstract

Nowadays, more and more organizations keep their valuable and sensitive data in Database Management Systems (DBMSs). The traditional database security mechanisms such as access control mechanisms, authentication, data encryption technologies do not offer a strong enough protection against the exploitation of vulnerabilities (e.g. intrusions) in DBMSs from insiders. Intrusion detection systems recently proposed in the literature focus on statistical approaches, which are not intuitive. Our research is the first ever effort to use process mining modeling low-level event logs for database intrusion detection. We have proposed a novel approach for visualizing database intrusion detection using process mining techniques. Our experiments showed that intrusion detection visualization will be able to help security officers who might not know deeply the complex system, identify the true positive detection and eliminate the false positive results.

Original language	English
Title of host publication	Intelligence and Security Informatics
Subtitle of host publication	Pacific Asia Workshop, PAISI 2012, Proceedings
Place of Publication	Germany
Publisher	Springer
Pages	81-95
Number of pages	15
ISBN (Electronic)	978-3-642-30428-6
ISBN (Print)	978-3-642-30427-9
DOIs	https://doi.org/10.1007/978-3-642-30428-6_7
Publication status	Published - 18 Jun 2012
Externally published	Yes
Event	Pacific Asia Workshop on Intelligence and Security Informatics (PAISI) 2012 - Kuala Lumpur, Malaysia Duration: 29 May 2012 → 29 May 2012 https://link.springer.com/book/10.1007/978-3-642-30428-6 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7299 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Workshop

Workshop	Pacific Asia Workshop on Intelligence and Security Informatics (PAISI) 2012
Abbreviated title	PAISI 2012
Country/Territory	Malaysia
City	Kuala Lumpur
Period	29/05/12 → 29/05/12
Internet address	https://link.springer.com/book/10.1007/978-3-642-30428-6 (Proceedings)

Keywords

conformance
database intrusion detection
event log
intrusion detection
intrusion detection visualization
Process mining
security

Access to Document

10.1007/978-3-642-30428-6_7

Cite this

Huynh, V., & Le, A. N. T. (2012). Process mining and security: Visualization in database intrusion detection. In Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2012, Proceedings (pp. 81-95). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7299 LNCS). Springer. https://doi.org/10.1007/978-3-642-30428-6_7

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title = "Process mining and security: Visualization in database intrusion detection",

abstract = "Nowadays, more and more organizations keep their valuable and sensitive data in Database Management Systems (DBMSs). The traditional database security mechanisms such as access control mechanisms, authentication, data encryption technologies do not offer a strong enough protection against the exploitation of vulnerabilities (e.g. intrusions) in DBMSs from insiders. Intrusion detection systems recently proposed in the literature focus on statistical approaches, which are not intuitive. Our research is the first ever effort to use process mining modeling low-level event logs for database intrusion detection. We have proposed a novel approach for visualizing database intrusion detection using process mining techniques. Our experiments showed that intrusion detection visualization will be able to help security officers who might not know deeply the complex system, identify the true positive detection and eliminate the false positive results.",

keywords = "conformance, database intrusion detection, event log, intrusion detection, intrusion detection visualization, Process mining, security",

author = "Viet Huynh and Le, {An N T}",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligence and Security Informatics",

note = "Pacific Asia Workshop on Intelligence and Security Informatics (PAISI) 2012, PAISI 2012 ; Conference date: 29-05-2012 Through 29-05-2012",

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Huynh, V & Le, ANT 2012, Process mining and security: Visualization in database intrusion detection. in Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7299 LNCS, Springer, Germany, pp. 81-95, Pacific Asia Workshop on Intelligence and Security Informatics (PAISI) 2012, Kuala Lumpur, Malaysia, 29/05/12. https://doi.org/10.1007/978-3-642-30428-6_7

Process mining and security: Visualization in database intrusion detection. / Huynh, Viet; Le, An N T.
Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2012, Proceedings. Germany: Springer, 2012. p. 81-95 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7299 LNCS).

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

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AB - Nowadays, more and more organizations keep their valuable and sensitive data in Database Management Systems (DBMSs). The traditional database security mechanisms such as access control mechanisms, authentication, data encryption technologies do not offer a strong enough protection against the exploitation of vulnerabilities (e.g. intrusions) in DBMSs from insiders. Intrusion detection systems recently proposed in the literature focus on statistical approaches, which are not intuitive. Our research is the first ever effort to use process mining modeling low-level event logs for database intrusion detection. We have proposed a novel approach for visualizing database intrusion detection using process mining techniques. Our experiments showed that intrusion detection visualization will be able to help security officers who might not know deeply the complex system, identify the true positive detection and eliminate the false positive results.

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KW - database intrusion detection

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Huynh V, Le ANT. Process mining and security: Visualization in database intrusion detection. In Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2012, Proceedings. Germany: Springer. 2012. p. 81-95. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-30428-6_7

Process mining and security: Visualization in database intrusion detection

Abstract

Publication series

Workshop

Keywords

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