人脸库提取与STP-CS相结合的多人脸图像压缩加密方案

IF 8.9 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Internet of Things Journal Pub Date : 2025-02-12 DOI:10.1109/JIOT.2025.3541228

Jun Mou;Linlin Tan;Yinghong Cao;Nanrun Zhou;Yushu Zhang

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引用次数: 0

摘要

随着互联网的飞速发展，人脸识别技术得到了广泛的应用，人脸数据库的保护就显得尤为重要。为了保护被识别的人脸，设计了一种基于电磁辐射Ktz神经元（ERKN）的多人脸图像压缩加密方案。因为只有人脸要加密，所以它们首先被提取出来。然后利用半张量积压缩感知（STP-CS）算法对人脸图像进行压缩，将压缩后的图像整合成一个大立方体，即三维立方体。然后，利用ERKN迭代生成的混沌序列，依次进行接口混淆算法、三维洗牌算法和三维扩散算法，最终得到密文图像立方体。对该方案进行了评价，在可行性和安全性方面表现良好。

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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Multiface Image Compression Encryption Scheme Combining Extraction With STP-CS for Face Database

With the rapid development of the Internet, face recognition technology is widely used, which makes the protection of face database especially important. To protect the recognized faces, a multiface image compression encryption (MFICE) scheme is designed based on the electromagnetic radiation Ktz neuron (ERKN). Since only faces are to be encrypted, they are first extracted. Then the face images are compressed by using semi-tensor product compressed sensing (STP-CS) algorithm, and the compressed images are integrated into a large cube, i.e., a 3-D cube. After that, interface confusion algorithm, 3-D shuffling algorithm, and 3-D diffusion algorithm are sequently performed by using chaotic sequences generated by iteration of ERKN, and finally the ciphertext image cube is obtained. The proposed scheme is evaluated, and it performs well in terms of feasibility and security.

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来源期刊

IEEE Internet of Things Journal Computer Science-Information Systems

CiteScore

17.60

自引率

13.20%

发文量

1982

期刊介绍： The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.