An overview of artificial intelligence based pattern matching in a security and digital forensic context

Faye Rona Mitchell

Research output: Chapter in Book/Report/Conference proceeding › Chapter

2 Citations (Scopus)

Abstract

Many real world security and digital forensics tasks involve the analysis of large amounts of data and the need to be able to classify parts of that data into sets that are not well or even easily defined. Rule based systems can work well and efficiently for simple scenarios where the security or forensics incident can be well specified. However, such systems do not cope as well where there is uncertainty, where the IT system under consideration is complex or where there is significant and rapid change in the methods of attack or compromise. Artificial Intelligence (AI) is an area of computer science that has concentrated on pattern recognition and in this extended abstract we highlighted some of the main themes in AI and their appropriateness for use in a security and digital forensics context.
Original languageEnglish
Title of host publicationCyberpatterns
PublisherSpringer
Pages215-222
Number of pages8
ISBN (Electronic)978-3-319-04447-7
ISBN (Print)978-3-319-04446-0
DOIs
Publication statusPublished - 2014

Fingerprint

Pattern matching
Artificial intelligence
Knowledge based systems
Computer science
Pattern recognition
Digital forensics
Uncertainty

Keywords

  • Knowledge Representation
  • Domain Ontology
  • Exploratory Data Analysis
  • Artificial Intelligence Technique
  • Bidirectional Associative Memory

Cite this

An overview of artificial intelligence based pattern matching in a security and digital forensic context. / Mitchell, Faye Rona.

Cyberpatterns. Springer, 2014. p. 215-222.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Mitchell, FR 2014, An overview of artificial intelligence based pattern matching in a security and digital forensic context. in Cyberpatterns. Springer, pp. 215-222. https://doi.org/10.1007/978-3-319-04447-7_17
Mitchell FR. An overview of artificial intelligence based pattern matching in a security and digital forensic context. In Cyberpatterns. Springer. 2014. p. 215-222 https://doi.org/10.1007/978-3-319-04447-7_17
Mitchell, Faye Rona. / An overview of artificial intelligence based pattern matching in a security and digital forensic context. Cyberpatterns. Springer, 2014. pp. 215-222
@inbook{93cab4347206443a848e31eeea9b8222,
title = "An overview of artificial intelligence based pattern matching in a security and digital forensic context",
abstract = "Many real world security and digital forensics tasks involve the analysis of large amounts of data and the need to be able to classify parts of that data into sets that are not well or even easily defined. Rule based systems can work well and efficiently for simple scenarios where the security or forensics incident can be well specified. However, such systems do not cope as well where there is uncertainty, where the IT system under consideration is complex or where there is significant and rapid change in the methods of attack or compromise. Artificial Intelligence (AI) is an area of computer science that has concentrated on pattern recognition and in this extended abstract we highlighted some of the main themes in AI and their appropriateness for use in a security and digital forensics context.",
keywords = "Knowledge Representation, Domain Ontology, Exploratory Data Analysis, Artificial Intelligence Technique, Bidirectional Associative Memory",
author = "Mitchell, {Faye Rona}",
year = "2014",
doi = "10.1007/978-3-319-04447-7_17",
language = "English",
isbn = "978-3-319-04446-0",
pages = "215--222",
booktitle = "Cyberpatterns",
publisher = "Springer",

}

TY - CHAP

T1 - An overview of artificial intelligence based pattern matching in a security and digital forensic context

AU - Mitchell, Faye Rona

PY - 2014

Y1 - 2014

N2 - Many real world security and digital forensics tasks involve the analysis of large amounts of data and the need to be able to classify parts of that data into sets that are not well or even easily defined. Rule based systems can work well and efficiently for simple scenarios where the security or forensics incident can be well specified. However, such systems do not cope as well where there is uncertainty, where the IT system under consideration is complex or where there is significant and rapid change in the methods of attack or compromise. Artificial Intelligence (AI) is an area of computer science that has concentrated on pattern recognition and in this extended abstract we highlighted some of the main themes in AI and their appropriateness for use in a security and digital forensics context.

AB - Many real world security and digital forensics tasks involve the analysis of large amounts of data and the need to be able to classify parts of that data into sets that are not well or even easily defined. Rule based systems can work well and efficiently for simple scenarios where the security or forensics incident can be well specified. However, such systems do not cope as well where there is uncertainty, where the IT system under consideration is complex or where there is significant and rapid change in the methods of attack or compromise. Artificial Intelligence (AI) is an area of computer science that has concentrated on pattern recognition and in this extended abstract we highlighted some of the main themes in AI and their appropriateness for use in a security and digital forensics context.

KW - Knowledge Representation

KW - Domain Ontology

KW - Exploratory Data Analysis

KW - Artificial Intelligence Technique

KW - Bidirectional Associative Memory

U2 - 10.1007/978-3-319-04447-7_17

DO - 10.1007/978-3-319-04447-7_17

M3 - Chapter

SN - 978-3-319-04446-0

SP - 215

EP - 222

BT - Cyberpatterns

PB - Springer

ER -

Access to Document