Joint compression and encryption of visual data using orthogonal parametric transforms

Author:

Puchala D.,Yatsymirskyy M. M.

Abstract

Abstract In this paper, we introduce a novel method of joint compression and encryption of visual data. In the proposed approach the compression stage is based on block quantization while the encryption uses fast parametric orthogonal transforms of arbitrary forms in combination with a novel scheme of intra-block mixing of data vectors. Theoretical analysis of the method indicates no impact of encryption stage on the effectiveness of block quantization with an additional step of first order entropy coding. Moreover, a series of experimental studies involving natural images and JPEG lossy compression standard were performed. Here, the obtained results indicate a high level of visual content concealment with only a small reduction of compression performance. An additional analysis of security allows to state that the proposed method is resistant to cryptanalytic attacks known for visual data encryption schemes including the most efficient NZCA attack. The proposed method can be also characterized by high computational efficiency and feasibility of hardware realizations.

Publisher

Walter de Gruyter GmbH

Subject

Artificial Intelligence,Computer Networks and Communications,General Engineering,Information Systems,Atomic and Molecular Physics, and Optics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3