An Image Encryption Technique Based on Logistic Sine Map and an Encrypted Image Retrieval Using DCT Frequency

Rajana Kanakaraju, Lakshmi V, S. S. Amiripalli, S. Potharaju, R. Chandrasekhar
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引用次数: 1

Abstract

In this digital era, most of the hospitals and medical labs are storing and sharing their medical data using third party cloud platforms for saving maintenance cost and storage and also to access data from anywhere. The cloud platform is not entirely a trusted party as the data is under the control of cloud service providers, which results in privacy leaks so that the data is to be encrypted while uploading into the cloud. The data can be used for diagnosis and analysis, for that the similar images to be retrieved as per the need of the doctor. In this paper, we propose an algorithm that uses discrete cosine transformation frequency and logistic sine map to encrypt an image, and the feature vector is computed on the encrypted image. The encrypted images are transferred to the cloud picture database, and feature vectors are uploaded to the feature database. Pearson’s Correlation Coefficient is calculated on the feature vector and is used as a measure to retrieve similar images. From the investigation outcomes, we can get an inference that this algorithm can resist against predictable attacks and geometric attacks with strong robustness.
基于逻辑正弦映射的图像加密技术及基于DCT频率的加密图像检索
在这个数字时代,大多数医院和医学实验室都在使用第三方云平台存储和共享医疗数据,以节省维护成本和存储空间,并从任何地方访问数据。由于数据处于云服务提供商的控制之下,云平台并不完全是受信任的一方,这导致隐私泄露,因此数据在上传到云时需要加密。这些数据可以用于诊断和分析,以便根据医生的需要检索相似的图像。本文提出了一种利用离散余弦变换频率和逻辑正弦映射对图像进行加密的算法,并在加密后的图像上计算特征向量。将加密后的图像传输到云图数据库中,将特征向量上传到特征数据库中。在特征向量上计算Pearson相关系数,并将其作为检索相似图像的度量。从研究结果可以推断,该算法可以抵抗可预测攻击和几何攻击,具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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