Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Data Protection on Mobile Applications


Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India
     

   Subscribe/Renew Journal


Piracy has been a huge problem to the entire IT industry. In the recent years there has been an increase in the usage of mobile based applications and many a times these applications have been illegally copied and used a lot. Apart from applications, piracy also affects video, audio producers, digital book etc. This results in huge revenue loss to the application developers and also in many cases causes the spread of viruses and backdoor programs causing hijacking of personal data. The most commonly pirated mobile apps are games and utility apps. In this paper we are proposing a new method of protecting mobile apps using steganography which will help in protecting the mobile apps against piracy.

Keywords

Data Protection, Steganography, Stego Image, Cover Image, LSB, MSB, RGB.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Mohammad A. Haque, Ramin Irani, Kamal Nasrollahi and Thomas B. Moeslund, “Heart Beat Rate Measurement from Facial Video”, IEEE Intelligent Systems, Vol. 31, No. 3, pp. 40-48, 2016.
  • H. Rahman and M.U. Ahmed, S. Begum and P. Funk, “Real Time Heart Rate Monitoring from Facial RGB Color Video using Webcam”, Proceedings of 29th Annual Workshop of the Swedish Artificial Intelligence Society, pp. 1-8, 2016.
  • Simmi Dutta, Hiteshwar, Abhimanyu Dev Jamwal and Azhar Ud Din Guroo, “Heart Rate Detection using Independent Component Analysis and Multivariate Adaptive Regression Splines”, Imperial Journal of Interdisciplinary Research, Vol. 2, No. 10, pp. 174-178, 2016.
  • M. Kumar, A. Veeraraghavan and A. Sabharwal, “Distance PPG: Robust Non-Contact Vital Signs Monitoring using A Camera”, Biomedical Optics Express, Vol. 6, No. 5, pp. 1565-1588, 2015.
  • Hussain A. Jaber, A.L. Ziarjawey and Ilyas Cankaya, “Heart Rate Monitoring and PQRST Detection Based on Graphical User Interface with Matlab”, International Journal of Information and Electronics Engineering, Vol. 5, No. 4, pp. 311-317, 2015.
  • J. Moreno, J. Ramos-Castro, J. Movellan, E. Parrado, G. Rodas and L. Capdevila, “Facial Video-based Photoplethysmography to Detect HRV at Rest”, International Journal of Sports Medicine, Vol. 36, No. 6, pp. 474-480, 2015.
  • Larissa Carvalho, H.G.Virani and S. Kutty, “Analysis of Heart Rate Monitoring Using a Webcam”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, No. 5, pp. 1-7, 2014.
  • X. Li, J. Chen, G. Zhao and M. Pietikainen, “Remote Heart Rate Measurement from Face Videos under Realistic Situations”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 4264-4271, 2014.
  • R. Irani, K. Nasrollahi and T.B. Moeslund, “Improved Pulse Dectection from Head Motions using DCT”, Proceedings of 9th International Conference on Computer Vision Theory and Applications, pp. 124-129, 2014.
  • S. Thulasi Prasad and S. Varadarajan, “Heart Rate Detection using Hilbert Transform”, International Journal of Research in Engineering and Technology, Vol. 2, No. 8, pp. 12-18, 2013.
  • Gerard De Haan and Vincent Jeanne, “Robust Pulse Rate from Chrominance-Based rPPG”, IEEE Transactions on Biomedical Engineering, Vol. 60, No. 10, pp. 94-128, 2013.
  • G. Balakrishnan, F. Durand and J. Guttag, “Detecting Pulse from Head Motions in Video”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 3430-3437, 2013.
  • X. Yu, J. Huang, S. Zhang, W. Yan and D. Metaxas, “Posefree Facial Landmark Fitting Via Optimized Part Mixtures and Cascaded Deformable Shape Model”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1944-1951, 2013.
  • Isayiyas Nigatu Tiba and Li Li, “Image-Based Automatic Pulse Rate Monitoring System Using PC Webcam”, International Journal of Engineering Research and Technology, Vol. 2, No. 12, pp. 841-847, 2013.
  • M. Soleymani, J. Lichtenauer, T. Pun and M. Pantic, “A Multimodal Database for Affect Recognition and Implicit Tagging”, IEEE Transactions on Affective Computing, Vol. 3, No. 1, pp. 42-55, 2012.

Abstract Views: 327

PDF Views: 0




  • Data Protection on Mobile Applications

Abstract Views: 327  |  PDF Views: 0

Authors

R. Rejani
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India
D. Murugan
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India

Abstract


Piracy has been a huge problem to the entire IT industry. In the recent years there has been an increase in the usage of mobile based applications and many a times these applications have been illegally copied and used a lot. Apart from applications, piracy also affects video, audio producers, digital book etc. This results in huge revenue loss to the application developers and also in many cases causes the spread of viruses and backdoor programs causing hijacking of personal data. The most commonly pirated mobile apps are games and utility apps. In this paper we are proposing a new method of protecting mobile apps using steganography which will help in protecting the mobile apps against piracy.

Keywords


Data Protection, Steganography, Stego Image, Cover Image, LSB, MSB, RGB.

References