Chaotic image encryption on GPU
Abstract
Several Chaotic Image Encryption algorithms have been proposed recently due to increase in the need of secure image/multimedia transmissions over public network. Even though chaotic image encryption algorithms perform better compared to normal cryptographic encryption techniques but still most of the algorithms require considerable amount of time which would increase the overall processing time. In this research we concentrated to achieve speed-up of chaotic encryption algorithm. We have shown a CUDA-based implementation of chaotic image encryption algorithm using logistic map with NVIDIA's Tesla C2050 GPU device. Compared to original implementation on CPU, CUDA based implementation works has shown significant amount of improvement in terms of operational speed up.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cited by
Sorted by citations
SPRING: a novel parallel chaos-based image encryption scheme
Lee, W.-K., Phan, R. C.-W., Yap, W.-S., & Goi, B.-M. (2018) · Nonlinear Dynamics · doi:10.1007/s11071-018-4076-6 · Cited by 65 · see citing works
GPU-Accelerated implementation of a genetically optimized image encryption algorithm
Bharadwaj, B., Saira Banu, J., Madiajagan, M., Ghalib, M. R., Castillo, O., & Shankar, A. (2021) · Soft Computing · doi:10.1007/s00500-021-06225-y · Cited by 14 · see citing works
“(Antwerpen 2011; Zafar et al. 2010) The paper also presents a genetic optimization exercise in detail, that was performed to enhance the security metrics of the PRNG, by the process of hyper-parameter tuning.”
Background
- Authors
- Vihari, P. L. V., & Mishra, M.
- Affiliations
- Indian Institute of Technology Roorkee (IN)
- ORCID
- Mishra, Manoj
- Venue
- Proceedings of the CUBE International Information Technology Conference
- Publisher
- ACM
- Published
- 2012-09-03
- Pages
- 753-758
- OpenAlex
- W2047000042
- Cited by
- 4
- References
- 0
- Citations by year
- 2021: 1 · 2020: 1 · 2018: 2
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CUBE International Information Technology Conference (CUBE) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Keywords
- chaotic image encryption, GPU acceleration, CUDA, logistic map, multimedia security
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
