Powered by OpenAIRE graph
Found an issue? Give us feedback
https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/117346...
Part of book or chapter of book . 2006 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1109/icmla....
Article . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2022
Data sources: DBLP
DBLP
Conference object . 2017
Data sources: DBLP
versions View all 4 versions
addClaim

Data Mining for Security Applications

Authors: Bhavani M. Thuraisingham;

Data Mining for Security Applications

Abstract

Data mining is the process of posing queries and extracting patterns, often previously unknown from large quantities of data using pattern matching or other reasoning techniques. Cyber security is the area that deals with cyber terrorism. We are hearing that cyber attacks will cause corporations billions of dollars. For example, one could masquerade as a legitimate user and swindle say a bank of billions of dollars. Data mining and web mining may be used to detect and possibly prevent security attacks including cyber attacks. For example, anomaly detection techniques could be used to detect unusual patterns and behaviors. Link analysis may be used to trace the viruses to the perpetrators. Classification may be used to group various cyber attacks and then use the profiles to detect an attack when it occurs. Prediction may be used to determine potential future attacks depending in a way on information learnt about terrorists through email and phone conversations. Also, for some threats non real-time data mining may suffice while for certain other threats such as for network intrusions we may need real-time data mining. Many researchers are investigating the use of data mining for intrusion detection. While we need some form of real-time data mining, that is, the results have to be generated in real-time, we also need to build models in real-time. For example, credit card fraud detection is a form of real-time processing. However, here models are built ahead of time. Building models in real-time remains a challenge. Data mining can also be used for analyzing web logs as well as analyzing the audit trails. Based on the results of the data mining tool, one can then determine whether any unauthorized intrusions have occurred and/or whether any unauthorized queries have been posed. There has been much research on data mining for intrusion detection. Data mining may also be applied for Biometrics related applications. Finally data mining has applications in national security including detecting and preventing terrorist activities. The presentation will provide an overview of data mining and security threats and then discuss the applications of data mining for cyber security and national security including in intrusion detection and biometrics. Privacy considerations including a discussion of privacy preserving data mining will also be given.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!