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Cited by 138Chaos-based Image/Signal EncryptionComputer Science and EngineeringCryptographic Implementations and Security

Analytical Study of Hybrid Techniques for Image Encryption and Decryption

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Chowdhary, Chiranji Lal, Patel, Pushpam Virenbhai, Kathrotia, Krupal Jaysukhbhai, Attique, Muhammad, Perumal, Kumaresan, Ijaz, Muhammad Fazal·2020·Sensors
DOI 10.3390/s20185162PMC PMC7570629
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Abstract

The majority of imaging techniques use symmetric and asymmetric cryptography algorithms to encrypt digital media. Most of the research works contributed in the literature focus primarily on the Advanced Encryption Standard (AES) algorithm for encryption and decryption. This paper propose an analysis for performing image encryption and decryption by hybridization of Elliptic Curve Cryptography (ECC) with Hill Cipher (HC), ECC with Advanced Encryption Standard (AES) and ElGamal with Double Playfair Cipher (DPC). This analysis is based on the following parameters: (i) Encryption and decryption time, (ii) entropy of encrypted image, (iii) loss in intensity of the decrypted image, (iv) Peak Signal to Noise Ratio (PSNR), (v) Number of Pixels Change Rate (NPCR), and (vi) Unified Average Changing Intensity (UACI). The hybrid process involves the speed and ease of implementation from symmetric algorithms, as well as improved security from asymmetric algorithms. ECC and ElGamal cryptosystems provide asymmetric key cryptography, while HC, AES, and DPC are symmetric key algorithms. ECC with AES are perfect for remote or private communications with smaller image sizes based on the amount of time needed for encryption and decryption. The metric measurement with test cases finds that ECC and HC have a good overall solution for image encryption.

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  • The entropy results generated by SCEC when applied to a series of well-known images surpassed the performance of other cryptosystems.

    “The entropy results generated by SCEC when applied to a series of well-known images surpassed the performance of other cryptosystems [30], [31].”

    From Cryptosystem Based on the Elliptic Curve With a High Degree of Resistance to Damage on the Encrypted Images (2020) · cites this paper as [31]

    Section 5.2 reports entropy measurements for the Eggs and Mona Lisa images, and the Conclusions state that the proposed hybrid algorithms achieved entropy values close to 8, better than existing algorithms. The paper evaluates ECC with Hill Cipher, ECC with AES, and ElGamal with Double Playfair Cipher—not SCEC—so it does not support attributing those results to SCEC. No page numbers were provided in our copy. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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References 32 · Cited by 138

Research works printed but not linked: 26

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Authors
Chowdhary, C. L., Patel, P. V., Kathrotia, K. J., Attique, M., Perumal, K., & Ijaz, M. F.
Affiliations
  • Vellore Institute of Technology University (IN)
  • Sejong University (KR)
Corresponding author
Ijaz, Muhammad Fazal
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2020-09-10
Volume
20
Issue
18
Pages
5162
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s20185162
PMC
PMC7570629
OpenAlex
W3084001442
Cited by
138
References
32
Citations by year
2026: 7 · 2025: 17 · 2024: 19 · 2023: 21 · 2022: 45 · 2021: 26 · 2020: 3
FWCI
9.23
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Sejong University
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
  • Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
  • Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
Keywords
image encryption, image decryption, hybrid encryption, elliptic curve cryptography, Hill cipher, Advanced Encryption Standard, ElGamal encryption, encryption and decryption time, image entropy, NPCR, UACI, PSNR

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