An embedded Bayesian Network Hidden Markov model for digital forensics

Olivier De Vel; Nianjun Liu; Terry Caelli; Tiberio S. Caetano

doi:10.1007/11760146_41

An embedded Bayesian Network Hidden Markov model for digital forensics

Olivier De Vel^*, Nianjun Liu, Terry Caelli, Tiberio S. Caetano

^*Corresponding author for this work

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

12 Citations (Scopus)

Abstract

In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the degree of criminal activity as it evolves over time. The model is evaluated with 500 randomly produced digital forensic scenarios and two specific forensic cases. The experimental results indicate that the model fits well with expert classification of forensic data. Such initial results point out the potential of such Dynamical Bayesian Network methods for the analysis of digital forensic data.

Original language	English
Title of host publication	Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings
Publisher	Springer Verlag
Pages	459-465
Number of pages	7
ISBN (Print)	3540344780, 9783540344780
DOIs	https://doi.org/10.1007/11760146_41
Publication status	Published - 2006
Externally published	Yes
Event	IEEE International Conference on Intelligence and Security Informatics, ISI 2006 - San Diego, CA, United States Duration: 23 May 2006 → 24 May 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3975 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	IEEE International Conference on Intelligence and Security Informatics, ISI 2006
Country/Territory	United States
City	San Diego, CA
Period	23/05/06 → 24/05/06

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10.1007/11760146_41

Cite this

De Vel, O., Liu, N., Caelli, T., & Caetano, T. S. (2006). An embedded Bayesian Network Hidden Markov model for digital forensics. In Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings (pp. 459-465). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3975 LNCS). Springer Verlag. https://doi.org/10.1007/11760146_41

De Vel, Olivier ; Liu, Nianjun ; Caelli, Terry et al. / An embedded Bayesian Network Hidden Markov model for digital forensics. Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings. Springer Verlag, 2006. pp. 459-465 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An embedded Bayesian Network Hidden Markov model for digital forensics",

abstract = "In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the degree of criminal activity as it evolves over time. The model is evaluated with 500 randomly produced digital forensic scenarios and two specific forensic cases. The experimental results indicate that the model fits well with expert classification of forensic data. Such initial results point out the potential of such Dynamical Bayesian Network methods for the analysis of digital forensic data.",

author = "{De Vel}, Olivier and Nianjun Liu and Terry Caelli and Caetano, {Tiberio S.}",

year = "2006",

doi = "10.1007/11760146_41",

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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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pages = "459--465",

booktitle = "Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings",

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note = "IEEE International Conference on Intelligence and Security Informatics, ISI 2006 ; Conference date: 23-05-2006 Through 24-05-2006",

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De Vel, O, Liu, N, Caelli, T & Caetano, TS 2006, An embedded Bayesian Network Hidden Markov model for digital forensics. in Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3975 LNCS, Springer Verlag, pp. 459-465, IEEE International Conference on Intelligence and Security Informatics, ISI 2006, San Diego, CA, United States, 23/05/06. https://doi.org/10.1007/11760146_41

An embedded Bayesian Network Hidden Markov model for digital forensics. / De Vel, Olivier; Liu, Nianjun; Caelli, Terry et al.
Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings. Springer Verlag, 2006. p. 459-465 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3975 LNCS).

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

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AB - In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the degree of criminal activity as it evolves over time. The model is evaluated with 500 randomly produced digital forensic scenarios and two specific forensic cases. The experimental results indicate that the model fits well with expert classification of forensic data. Such initial results point out the potential of such Dynamical Bayesian Network methods for the analysis of digital forensic data.

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DO - 10.1007/11760146_41

M3 - Conference contribution

SN - 3540344780

SN - 9783540344780

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings

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De Vel O, Liu N, Caelli T, Caetano TS. An embedded Bayesian Network Hidden Markov model for digital forensics. In Intelligence and Security Informatics - IEEE International Conference on Intelligence and Security Informatics, ISI 2006, Proceedings. Springer Verlag. 2006. p. 459-465. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11760146_41

An embedded Bayesian Network Hidden Markov model for digital forensics

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