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Multimedia Tools and Applications

, Volume 77, Issue 16, pp 20385–20414 | Cite as

Hyper-chaotic Feeded GA (HFGA): a reversible optimization technique for robust and sensitive image encryption

  • Parisa Gholizadeh Pashakolaee
  • Hadi Shahriar Shahhoseini
  • Morteza Mollajafari
Article

Abstract

In recent years, due to their straightforward structure and efficiency, the chaos-based cryptographic algorithms have become a good candidate for image encryption. However, they still suffer from many weaknesses, such as insensitivity to the plain image, weak key streams, small key space, non-resistance to some attacks and failure to meet some security criteria. For this purpose in this paper, a novel hybrid image encryption algorithm named Hyper-chaotic Feeded GA (HFGA) is proposed to fill the gaps in two stages; initial encryption by using a hyper-chaotic system, and then outputs reinforcement by employing a customized Genetic Algorithm (GA). By applying an innovative technique, called gene-labelling, the proposed algorithm not only optimizes the preliminary encrypted images in terms of security criteria but also allows the legal receiver to easily and securely decrypt the optimized cipher image. In fact, in the first stage, besides unpredictable random sequences generated by a hyper-chaotic system, a new sensitive diffusion function is proposed which makes the algorithm resistant to differential attacks. In the second stage, the generated cipher images, which are labeled in a special way, will be used as the initial population of a GA which enhances randomness of the cipher images. The results of several experiments and statistical analysis show that the proposed image encryption scheme provides an efficient and secure way for fast image encrypting as well as providing robustness against some well-known statistical attacks.

Keywords

Image encryption Genetic algorithm Hyper-chaotic system Security evaluation 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Parisa Gholizadeh Pashakolaee
    • 1
  • Hadi Shahriar Shahhoseini
    • 1
  • Morteza Mollajafari
    • 1
  1. 1.School of Electrical EngineeringIran University of Science and TechnologyTehranIran

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