PROTECTING PRIVATE DATA ON MOBILE SYSTEMS BASED ON SPATIO–TEMPORAL ANALYSIS

Sausan Yazji, Robert P. Dick, Peter Scheuermann, Goce Trajcevski

Abstract

Mobile devices such as smart phones and laptops are in common use and carry a vast amount of personal data. This paper presents an efficient behavior-based system for rapidly detecting the theft of mobile devices in order to protect the private data of their users. Our technique uses spatio-temporal information to construct models of user motion patters. These models are used to detect theft, which may produce anomalous spatio-temporal patterns. We consider two types of user models, each of which builds on the relationship between location and time of day. Our evaluation, based on the Reality Mining dataset, shows that our system is capable of detecting an attack within 15 minutes with 81% accuracy.

References

  1. Alvares, L. O., Bogorny, V., Kuijpers, B., de Macedo, J. A. F., Bart, B., and Vaisman, A. (2007). A model for enriching trajectories with semantic geographical information. In GIS 7807: Proceedings of the 15th International Symposium on Advances in Geographic Information Systems. ACM.
  2. Chen, L. D. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1):32-52.
  3. Dodge, S., Weibel, R., and Forootan, E. (2009). Revealing the physics of movement: Comparing the similarity of movement characteristics of different types of moving objects. Computers, Environment and Urban Systems, 33(6):419-434.
  4. Eagle, N., Pentland, A., and Lazer, D. (2007). Inferring social network structure using mobile phone data. Proceedings of the National Academy of Sciences (PNAS), 106(36):15274-15278.
  5. GadgetTrak (2010). GadgetTrak System. http://www. gadgettrak.com/.
  6. Gómez, L. I., Kuijpers, B., and Vaisman, A. (2008). Querying and mining trajectory databases using places of interest. In Annals of Information Systems, volume 3.
  7. González, M. C., Hidalgo, C. A., and Barabási, A. L. (2008). Understanding individual human mobility patterns. Nature, 453:479.
  8. Güting, R. H. and Schneider, M. (2005). Moving Objects Databases. Morgan Kaufmann.
  9. Hadjieleftheriou, M., Kollios, G., Bakalov, P., and Tsotras, V. J. (2005). Complex spatio-temporal pattern queries. In VLDB 05: Proceedings of the 31st International Conference on Very Large Databases. ACM.
  10. Hall, J., Barbeau, M., and Kranakis, E. (2005). Anomalybased intrusion detection using mobility profiles of public transportation users. In WiMob'05: Proceedings of the Wireless and Mobile Computing, Networking and Communications. IEEE.
  11. Hung, C., Chang, C., and Peng, W. (2009). Mining trajectory profiles for discovering user communities. In LBSN 7809: Proceedings of the 2009 International Workshop on Location Based Social Networks. ACM.
  12. Jeung, H., Liu, Q., Shen, H. T., and Zhou, X. (2008). A hybrid prediction model for moving objects. In ICDE 7808: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering. IEEE.
  13. LaptopCop (2010). Laptop Cop Software. http://www.laptopcopsoftware.com/index.html.
  14. Monitoring, M. S. (2010). Windows mobile security monitoring software. http://www.recoverycop.com/index. html.
  15. Mouza, C. D. and Rigaux, P. (2005). Mobility patterns. GeoInformatica, 9(4):297-319.
  16. OSM (2010). Open street map. http://www.OpenStreetMap .org.
  17. Rhee, I., Shin, M., Hong, S., Lee, K., and Chong, S. (2008). On the Levy-Walk nature of human mobility. In INFOCOM 7808: Proceeding of the IEEE Conference on Computer Communications. IEEE.
  18. Sun, B., Yu, F., Wu, K., Xiao, Y., and Leung, V. (2007). Enhancing security using mobility-based anomaly detection in cellular mobile networks. In IEEE Transactions on Vehicular Technology, volume 55, pages 1385 -1396.
  19. Thornton, P. and Houser, C. (2004). Using mobile phones in education. In WMTE 7804: Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education. IEEE.
  20. Trestian, I., Ranjan, S., Kuzmanovic, A., and Nucci, A. (2009). Measuring serendipity: Connecting people, locations and interests in a mobile 3g network. In IMC 7809: Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement. ACM.
  21. Xie, K., Deng, K., and Zhou, X. (2009). From trajectories to activities: a spatio-temporal join approach. In LBSN 7809: Proceedings of the 2009 International Workshop on Location Based Social Networks, Seattle, Washington. ACM.
  22. Yan, G., Eidenbenz, S., and Sun, B. (2009). Mobiwatchdog: You can steal, but you can't run! In WiSec 7809: Proceedings of the Second ACM Conference on Wireless Network Security. ACM.
  23. Yazji, S., Chen, X., Dick, R. P., and Scheuermann, P. (2009). Implicit user re-authentication for mobile devices. In UIC 7809: Proceedings of the 6th International Conference on Ubiquitous Intelligence and Computing, pages 325-339. Springer-Verlag.
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Paper Citation


in Harvard Style

Yazji S., P. Dick R., Scheuermann P. and Trajcevski G. (2011). PROTECTING PRIVATE DATA ON MOBILE SYSTEMS BASED ON SPATIO–TEMPORAL ANALYSIS . In Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-8425-48-5, pages 114-123. DOI: 10.5220/0003373301140123


in Bibtex Style

@conference{peccs11,
author={Sausan Yazji and Robert P. Dick and Peter Scheuermann and Goce Trajcevski},
title={PROTECTING PRIVATE DATA ON MOBILE SYSTEMS BASED ON SPATIO–TEMPORAL ANALYSIS},
booktitle={Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2011},
pages={114-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003373301140123},
isbn={978-989-8425-48-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - PROTECTING PRIVATE DATA ON MOBILE SYSTEMS BASED ON SPATIO–TEMPORAL ANALYSIS
SN - 978-989-8425-48-5
AU - Yazji S.
AU - P. Dick R.
AU - Scheuermann P.
AU - Trajcevski G.
PY - 2011
SP - 114
EP - 123
DO - 10.5220/0003373301140123