Abstract
Original language | English |
---|---|
Title of host publication | Cyberpatterns |
Publisher | Springer |
Pages | 215-222 |
Number of pages | 8 |
ISBN (Electronic) | 978-3-319-04447-7 |
ISBN (Print) | 978-3-319-04446-0 |
DOIs | |
Publication status | Published - 2014 |
Fingerprint
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
}
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 -