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Systematic Survey on Visually Meaningful Image Encryption Techniques

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Abstract
Due to advancements in technology, digital images are widely used in various applications like medical field, military communication, remote sensing, etc. These images may contain sensitive and confidential information. Therefore, images are required to be protected from unauthorized access. Many image protection techniques have been proposed in past years. The most common technique to protect the images is encryption. In this technique, a secret key and an encryption algorithm are used to change the plain image into an encrypted image. The encrypted image looks like a noisy image and can easily attract the attacker's attention. If an image gets captured and stacked, sensitive information can be revealed. In this regard, Visually Meaningful Encrypted Image (VMEI) technique is developed, which initially encrypts the original image and then hides it into a reference image. The final encrypted image looks like a normal image. Hence, the VMEI technique provides more security as compared to simple image encryption techniques. Therefore, a systematic survey of existing VMEI techniques is presented in this paper. The VMEI techniques are divided into different categories based on their characteristics. Moreover, this paper elaborates and investigates the improvements and analyses performed on VMEI techniques based on various evaluation parameters. These evaluation parameters are divided into different categories such as security attacks, encryption key attacks, quality analysis, and noise attacks. Finally, this paper discusses the potential applications and future challenges of VMEI techniques.
Author(s)
Himthani, VarshaDhaka, Vijaypal SinghKaur, ManjitSingh, DilbagLee, Heung-No
Issued Date
2022-01
Type
Article
DOI
10.1109/ACCESS.2022.3203173
URI
https://scholar.gist.ac.kr/handle/local/11056
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE ACCESS, v.10, pp.98360 - 98373
ISSN
2169-3536
Appears in Collections:
Department of Electrical Engineering and Computer Science > 1. Journal Articles
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