Abstract
Most contemporary tracking applications consider an online approach where the target is tracked in real time. In criminal investigations, however, it is often the case that only offline tracking is possible, i.e., tracking takes place after the fact. In offline tracking, given an incomplete trace of a target, the task is to reconstruct the missing parts and obtain the full trace. The proliferation of modern transportation systems means that a targeted entity is likely to use multiple modes of transportation. This paper introduces a class of mobility models tailored for forensic analysis. The mobility models are used to construct a multi-modal forensic tracking system that can reconstruct a complete trace of a target. Theoretical analysis of the reconstruction algorithm demonstrates that it is both complete and optimal.
Chapter PDF
References
S. Al-Kuwari and S. Wolthusen, Probabilistic vehicular trace reconstruction based on RF-visual data fusion, Proceedings of the Eleventh IFIP TC 6/TC 11 International Conference on Communications and Multimedia Security, pp. 16–27, 2010.
S. Al-Kuwari and S. Wolthusen, Fuzzy trace validation: Toward an offline forensic tracking framework, Proceedings of the Sixth IEEE International Workshop on Systematic Approaches to Digital Forensic Engineering, 2011.
A. Dempster, N. Laird and D. Rubin, Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B (Methodological), vol. 39(1), pp. 1–38, 1977.
W. Gilks, S. Richardson and D. Spiegelhalter (Eds.), Markov Chain Monte Carlo in Practice, Chapman and Hall/CRC Press, Boca Raton, Florida, 1996.
J. Harri, F. Filali and C. Bonnet, Mobility models for vehicular ad hoc networks: A survey and taxonomy, IEEE Communications Surveys and Tutorials, vol. 11(4), pp. 19–41, 2009.
D. Helbing and P. Molnar, Social force model for pedestrian dynamics, Physical Review E, vol. 51(5), pp. 4282–4286, 1995.
M. Tanner and W. Wong, The calculation of posterior distributions by data augmentation, Journal of the American Statistical Association, vol. 82(398), pp. 528–540, 1987.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Al-Kuwari, S., Wolthusen, S. (2012). Forensic Tracking and Mobility Prediction in Vehicular Networks. In: Peterson, G., Shenoi, S. (eds) Advances in Digital Forensics VIII. DigitalForensics 2012. IFIP Advances in Information and Communication Technology, vol 383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33962-2_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-33962-2_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33961-5
Online ISBN: 978-3-642-33962-2
eBook Packages: Computer ScienceComputer Science (R0)