CFP last date
20 January 2025
Reseach Article

Privacy Preservation of Mobile Data using Matrix Transformation

by Sabarish B A, Pradisa S, Nithyasri J
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 14
Year of Publication: 2014
Authors: Sabarish B A, Pradisa S, Nithyasri J
10.5120/15274-3865

Sabarish B A, Pradisa S, Nithyasri J . Privacy Preservation of Mobile Data using Matrix Transformation. International Journal of Computer Applications. 87, 14 ( February 2014), 8-13. DOI=10.5120/15274-3865

@article{ 10.5120/15274-3865,
author = { Sabarish B A, Pradisa S, Nithyasri J },
title = { Privacy Preservation of Mobile Data using Matrix Transformation },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 14 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number14/15274-3865/ },
doi = { 10.5120/15274-3865 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:53.448750+05:30
%A Sabarish B A
%A Pradisa S
%A Nithyasri J
%T Privacy Preservation of Mobile Data using Matrix Transformation
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 14
%P 8-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data leakage from mobile phones and LBS is increasing with the exponential growth of technology, resulting in an innate risk of privacy threats. To address this issue, a novel method to protect user privacy is proposed in this paper. The proposed algorithms, namely SSET and SIMET, provide efficient means to encrypt the SIM and IMEI numbers respectively, thus protecting user identity. The reverse procedure to retrieve the numbers is provided by the algorithms SSDT and SIMDT and illustrated with examples. The main objective of this work is to secure the privacy of mobile phone users by employing optimal cryptographic techniques.

References
  1. Favell, Andy. 2013. Global mobile statistics 2013 Part A: Mobile subscribers; handset market share; mobile operators. http://mobithinking. com/mobile/mobile-marketing-tools/latest-mobile-stats/a.
  2. Ciriani, V. , Vimercati, De Capitani di. , Foresti, S. , and Samarati, P. K-Anonymity. 2007. Advances in Information Security. Springer US.
  3. Gkoulalas-Divanis, Aris and Verykios, Vassilios S. 2009. Exact Knowledge Hiding through Database Extension. IEEE Transactions on Knowledge and Data Engineering, Vol. 21, No. 5.
  4. Sweeney, Latanya. 2002. K-Anonymity: A Model for protecting Privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems. 10 (5): 557-570.
  5. Tung, Liam. 2013. Google Play privacy slip-up sends app buyers' personal details to developers. http://www. zdnet. com/google-play-privacy-slip-up-sends-app-buyers-personal-details-to-developers-7000011249/
  6. Gagnon, Michael N. 2011. Hashing IMEI numbers does not protect privacy. http://blog. dasient. com/2011/07/hashing-imei-numbers-does-not-protect. html
  7. Angwin, Julia. 2012. What They Know- Mobile series, The Wall Street Journal. http://blogs. wsj. com/wtk­mobile/
  8. Gidofalvi, Gyozo. , Huang, Xuegang and Pedersen, Torben Bach. 2007. Privacy-Preserving Data Mining on Moving Object Trajectories. IEEE.
  9. Dong, Changyu and Dulay, Naranker. 2011. Longitude: a Privacy­ preserving Location Sharing Protocol for Mobile Applications. IFIP Advances in Information and Communication Technology.
  10. Khoshgozaran, Ali. , Shahabi, Cyrus and Shirani-Mehr, Houtan. 2010. Location privacy: going beyond K-anonymity, cloaking and anonymizers. Springer-Verlag London.
  11. Rahul. 2009. Tracking and Positioning of mobile devices in Telecommunication networks. http://www. slideshare. net/rahul_2013/tracking­and­positioning­of­mobile­systems­in­telecommunication­networks­15633468
  12. Fitchard, Kevin. 2012. The super-computing phone: At&T's predictions for devices in 2020. http:://gigaom. com/2012/09/10/the-super-computing-phone-atts-predictions-for-devices-in-2020/
  13. Samarati, Pierangela. 2008. K-anonymity. Foundations of Security Analysis and Design (FOSAD).
  14. Admin. 2010. IMEI Structure. IMEI Tools- Analysis tools, manuals, instructions. http://imei­number. com/imei­structure/
  15. Vijayarani, S. , and Tamilarasi, A. 2010. K-Anonymity Techniques - A Review. International Journal of Computer Science and Application.
  16. Wernke, Marius. , Skyortsov, Pavel. , et al. 2012. A classification of location privacy attacks and Approaches. Springer.
  17. Pei, Jian. , Tao, Yufei. , et al . 2009. Privacy Preserving Publishing on Multiple Quasi-Identifiers. Proceedings of the Twenty-fifth IEEE International Conference on Data Engineering (ICDE'09).
  18. Motwani, Rajeev and Xu, Ying. 2008. Efficient Algorithms for Masking and Finding Quasi­Identifiers.
  19. Pai, Sameer. , Bermudez, Sergio. , et al. 2008. Transactional Confidentiality in sensor Networks. IEEE Security and Privacy.
Index Terms

Computer Science
Information Sciences

Keywords

Privacy preserving mobile data security