Cryptanalysis on an image scrambling encryption scheme based on pixel bit

Liang Zhao, Avishek Adhikari, Di Xiao, Kouichi Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


Recently, an image scrambling encryption algorithm which makes use of one-dimensional chaos system for shuffling the pixel bits was proposed in [G.-D. Ye, Pattern Recognition Lett. 31(2010) 347-354]. Through the scrambling algorithm, the pixel locations and values can be encrypted at the same time. This scheme can be thought of as a typical binary image scrambling encryption considering the bit-plain of size Mx8. In [Li C.Q., Lo K. T.,], Li et al. proposed an attack using more than [log2(8MN-1)] many known-plaintext images to recover the original plain image with the noise of size M x N. The same principle is also suitable for the chosen-plaintext attack which can obtain the exact plain image. In the current paper, a simple attack on the original scheme is presented by applying chosen-plaintext images. Using our attack, the encryption vectors TM and TN and the decryption vectors TM′ and TN′ can be recovered completely. The experimental simulations on two standard images of size 128 x 128 and 256 x 256 justify our analysis. It is shown that the recovered images are identical with the corresponding original images. For both the original images, the number of chosen-plaintext images required in our scheme is 9, where as to do the same using the scheme proposed in Li et al.' attack, at least 17 and 19 chosen-plaintext images there will be required respectively. Moreover, the some method can be also used for chosen-ciphertext attack which reveals the decryption vectors TM′ and TN′ directly. Note that our attacks are also successful under iteration system which is remarked in the conclusions.

Original languageEnglish
Title of host publicationDigital Watermarking - 9th International Workshop, IWDW 2010, Revised Selected Papers
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783642184048
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6526 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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