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Cryptanalyzing an image encryption algorithm based on autoblocking and electrocardiography
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Li, Chengqing, Lin, Dongdong, Lü, Jinhu and Hao, Feng (2018) Cryptanalyzing an image encryption algorithm based on autoblocking and electrocardiography. IEEE MultiMedia , 25 (4). pp. 46-56. doi:10.1109/mmul.2018.2873472 ISSN 1070-986X.
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Official URL: https://doi.org/10.1109/mmul.2018.2873472
Abstract
This paper performs a thorough security analysis of a chaotic image encryption algorithm based on autoblocking and electrocardiography from the view point of modern cryptography. The algorithm uses electrocardiography (ECG) signals to generate the initial key for a chaotic system and applies an autoblocking method to divide a plain image into blocks of certain sizes suitable for subsequent encryption. The designers claimed that the proposed algorithm is “strong and flexible enough for practical applications”. We find it is vulnerable to the known plaintext attack: based on one pair of a known plain-image and its corresponding cipher-image, an adversary is able to derive a mask image, which can be used as an equivalent secret key to successfully decrypt other cipher images encrypted under the same key with a non-negligible probability of 1/256. Using this as a typical counterexample, we summarize some security defects existing in many image encryption algorithms.
Item Type: | Journal Article | |||||||||
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Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||
Library of Congress Subject Headings (LCSH): | Cryptography, Image processing -- Security measures, Data encryption (Computer science) , Image processing -- Digital techniques | |||||||||
Journal or Publication Title: | IEEE MultiMedia | |||||||||
Publisher: | IEEE Computer Society | |||||||||
ISSN: | 1070-986X | |||||||||
Official Date: | 1 October 2018 | |||||||||
Dates: |
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Volume: | 25 | |||||||||
Number: | 4 | |||||||||
Page Range: | pp. 46-56 | |||||||||
DOI: | 10.1109/mmul.2018.2873472 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Reuse Statement (publisher, data, author rights): | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||
Date of first compliant deposit: | 21 December 2018 | |||||||||
Date of first compliant Open Access: | 21 December 2018 | |||||||||
RIOXX Funder/Project Grant: |
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