Research Article
A Hybrid Lossy Compression Using 2-D Discrete Cosine Transform and Visual Cryptographic Technique for Security of Multimedia Image Data Communications in Internet of Things
@INPROCEEDINGS{10.1007/978-3-319-66742-3_28, author={Quist-Aphetsi Kester}, title={A Hybrid Lossy Compression Using 2-D Discrete Cosine Transform and Visual Cryptographic Technique for Security of Multimedia Image Data Communications in Internet of Things}, proceedings={e-Infrastructure and e-Services for Developing Countries. 8th International Conference, AFRICOMM 2016, Ouagadougou, Burkina Faso, December 6-7, 2016, Proceedings}, proceedings_a={AFRICOMM}, year={2017}, month={10}, keywords={Internet of things Digital images Security Encryption Compression Discrete cosine transforms}, doi={10.1007/978-3-319-66742-3_28} }- Quist-Aphetsi Kester
Year: 2017
A Hybrid Lossy Compression Using 2-D Discrete Cosine Transform and Visual Cryptographic Technique for Security of Multimedia Image Data Communications in Internet of Things
AFRICOMM
Springer
DOI: 10.1007/978-3-319-66742-3_28
Abstract
Security in internet of things is very critical. The computer systems that use image acquisition and processing from onboard or remote systems need to secure image data over the internet. Security of multimedia image data transmitted over secured and unsecured communications channel in today’s cyberspace is of paramount consideration due to malicious activities over these channels and there has been a high demand especially for end to end security applications for mobile devices. This is to ensure safety and security as well as privacy to transmitted data and stored data in the clouds. In this paper, we proposed a hybrid approach for securing digital images for devices by engaging lossy compression using 2-D discrete cosine transform and Visual Cryptographic Technique. The DCT was used for the lossy compression process and the visual cryptography was used to encrypt the image for confidentiality. The results showed to be very effective and the implementation was done using MATLAB.