Parallel implementation of rotation visual cryptography on GPU using CUDA

Veena Mayya, Aparna Nayak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Visual cryptography scheme (VCS), is a cryptography technique where visual information is encrypted in such a way that decryption can be fulfilled with human visual system by direct stacking of the encrypted shares. Rotation visual cryptography is advanced technique of VCS where direct stacking of shares will not uphold the original image. In the existing literature, encryption techniques of VCS take longer time that can be substantially reduced by using CUDA. The proposed method uses CUDA for computationally intensive independent tasks performed on pixels during the rotation VCS. Parallel implementation of VCS will be faster and can be adopted in many real time applications that requires image security. Results show that the proposed method is 40-50 times faster than the existing encryption techniques.

Original languageEnglish
Title of host publicationProceedings of 2017 International Conference on Advances in Image Processing, ICAIP 2017
PublisherAssociation for Computing Machinery (ACM)
Pages62-65
Number of pages4
VolumePart F131200
ISBN (Electronic)9781450352956
DOIs
Publication statusPublished - 25-08-2017
Event2017 International Conference on Advances in Image Processing, ICAIP 2017 - Bangkok, Thailand
Duration: 25-08-201727-08-2017

Conference

Conference2017 International Conference on Advances in Image Processing, ICAIP 2017
CountryThailand
CityBangkok
Period25-08-1727-08-17

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Mayya, V., & Nayak, A. (2017). Parallel implementation of rotation visual cryptography on GPU using CUDA. In Proceedings of 2017 International Conference on Advances in Image Processing, ICAIP 2017 (Vol. Part F131200, pp. 62-65). Association for Computing Machinery (ACM). https://doi.org/10.1145/3133264.3133280