An embedded Bayesian Network Hidden Markov model for digital forensics

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

Volumn 3975 LNCS, Issue , 2006, Pages 459-465

  De Vel, Olivier ^a   Liu, Nianjun ^b   Caelli, Terry ^b   Caetano, Tiberio S ^b  

^a DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

^b CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); EMBEDDED SYSTEMS; INFORMATION USE; KNOWLEDGE BASED SYSTEMS; MARKOV PROCESSES; TRACKING (POSITION);

BAYESIAN NETWORK; FORENSIC CASES; FORENSIC SCENARIOS; HIDDEN MARKOV MODEL;

DATA REDUCTION;

EID: 33745893503     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11760146_41     Document Type: Conference Paper

References (6)

1. Casey, Eoghan, "Digital Evidence and Computer Crime: Forensic Science", Computer and the Internet, Academic Press, 2000.
2. C. Apte, F. Damerau, "Automated learning of decision rules for text categorization", ACM Transactions on Information Systems, Vol 12, No.3, pp.233-251, 1994.
3. L. R. Rabiner, "A tutorial on Hidden Markov Models and selected applications in speech recognition". Proc. of the IEEE, 77(2):257-286, 1989.
4. F. V. Jensen. Bayesian Networks and Decision Graphs. Springer-Verlag, 2001.
5. Y. Linde, A. Buzo, and R.M. Gray, "An algorithm for vector quantizer design", IEEE Transactions on. Communications, vol 28, pp. 84-95, Jan 1980.
6. G.D. Forney, "The Viterbi algorithm", Proc.IEEE, vol 61, pp.268-278, Mar 1973.