Skip to main content
SpringerLink
Log in

Optimized Two-Dimensional Chaotic Mapping for Enhanced Image Security Using Sea Lion Algorithm

  • Conference paper
  • First Online:
Emerging Research in Computing, Information, Communication and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 790))

Abstract

With the rapid progression of digital image processing and network communication, information security issues have become ever more outstanding. Image encryption has to turn out to be an imperative research direction. Till now, countless scholars have projected copious image encryption algorithms based on chaos systems. However, the low-dimensional chaotic sequences have the troubles of shortcode period and low accuracy, which cannot assure the algorithm security. Thus, this paper intends to propose an optimized two-dimensional (2D) chaotic mapping (O2DCM) for image encryption. Here, the initial chaotic system parameters are fine-tuned with a new optimization algorithm referred as the average fitness-based Sea Lion optimization algorithm (AF-SLnO), which is an improved version of standard Sea Lion optimization algorithm (SLnO). The chaotic key generation system is nothing but the proposed AF-SLnO attempts to maximize the information entropy model. As a result, optimal initial parameters for the chaotic system can be determined. The security improvement is demonstrated using standard security analysis such as key sensitivity analysis, histogram analysis and adjacent pixel autocorrelation tests.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

Abbreviation :

Description

T-DES:

Triple-Data Encryption Standard

IDEA:

International Data Encryption Algorithm

DES:

Data Encryption Standard

AES:

Advanced Encryption Standard

PTSTFrFT:

Phase-Truncated Short-Time Fractional Fourier Transform

EU:

Encryption Unit

MGA:

Modified Genetic Algorithm

CTM:

Chaotic Tent Map

LTM:

Logistic-Tent Map

DNA:

Deoxyribonucleic Acid Coding

ECC:

Elliptic Curve Cryptosystem

CKC-NN:

Chaotic Key Controlled Neural Networks

KCFF-NN:

Key Controlled Finite Field Neural Network

LDMLNCML:

Logistic-Dynamic Mixed Linear-Nonlinear Coupled Map Lattices

2D:

Two Dimensional

AF-SLnO:

Average Fitness-Based Sea Lion Optimization Algorithm

SLnO:

Sea Lion Optimization Algorithm

H-CS:

Hyper-Chaotic System

HS-IEA:

High-Sensitivity Image Encryption Algorithm

IEA:

Image Encryption Algorithm

PP and CB:

Phase Portrait and Chaotic Behaviors

2D-LM:

2D- Logistic Map

CS:

Chaotic System

LD:

Logistic Diffusion

LT:

Logistic Transposition

LP:

Logistic Permutation

LSG:

Logistic sequence generator

References

  1. Dou S, Shen X, Zhou B, Wang L, Lin C (2019) Experimental research on optical image encryption system based on joint Fresnel transform correlator. Opt Laser Technol 112:56–64

    Article  Google Scholar 

  2. Liu J, Bai T, Shen X, Dou S, Ying J (2018) Parallel encryption and hierarchical retrieval for multi-channel images using an optical joint Fresnel transform correlator. Opt Commun 426:497–505

    Article  Google Scholar 

  3. Cai J, Shen X, Fan C, Zhou B (2019) Security-enhanced optical encryption based on JTC architecture with confused ciphertext. Optik Commun

    Google Scholar 

  4. Chen C, Sun K, He S (2020) An improved image encryption algorithm with finite computing precision. Signal Proc 168:107340

    Article  Google Scholar 

  5. Huang ZJ, Cheng S, Gong LH, Zhou NR (2020) Nonlinear optical multi-image encryption scheme with two-dimensional linear canonical transform. Opt Lasers Eng 124:105821

    Article  Google Scholar 

  6. Ghadirli HM, Nodehi A, Enayatifar R (2019) An overview of encryption algorithms in color images. Signal Proc 164:163–185

    Article  Google Scholar 

  7. Leihong Z, Zhisheng Z, Yi K, Hualong Y, Dawei Z (2020) Research on double-layers optical information encryption based on ghost imaging. Opt Commun 455:124585

    Article  Google Scholar 

  8. Babaei A, Motameni H, Enayatifar R (2019) A new permutation-diffusion-based image encryption technique using cellular automata and DNA sequence. Optik Commun 203:164000

    Article  Google Scholar 

  9. Bentoutou Y, Bensikaddour EH, Taleb N, Bounoua N (2019) An improved image encryption algorithm for satellite applications. Adv Space Res Commun

    Google Scholar 

  10. Yang F, Mou J, Liu J, Ma C, Yan H (2020) Characteristic analysis of the fractional-order hyperchaotic complex system and its image encryption application. Signal Proc 169:107373

    Article  Google Scholar 

  11. Ben Farah MA, Guesmi R, Kachouri A, Samet M (2020) A novel chaos based optical image encryption using fractional Fourier transform and DNA sequence operation. Opt Laser Technol 121:105777

    Article  Google Scholar 

  12. Mahmud M, Rahman A, Lee M, Choi JY (2020) Evolutionary-based image encryption using RNA codons truth table. Opt Laser Technol 121:105818

    Article  Google Scholar 

  13. Zhang D, Zhang F (2014) Chaotic encryption and decryption of JPEG image. Optik—Int J Light Electron Opt 125(2):717–720

    Article  Google Scholar 

  14. Banik A, Shamsi Z, Laiphrakpam DS (2019) An encryption scheme for securing multiple medical images. J Inf Secur Appl 49:102398

    Google Scholar 

  15. Li CL, Li ZY, Feng W, Tong YN, Wei DQ (2019) Dynamical behavior and image encryption application of a memristor-based circuit system. AEU—Int J Electron Commun 110:152861

    Article  Google Scholar 

  16. Liansheng S, Cong D, Xiao Z, Ailing T, Anand A (2019) Double-image encryption based on interference and logistic map under the framework of double random phase encoding. Opt Lasers Eng 122:113–122

    Article  Google Scholar 

  17. Zhang X, Li W, Hu H, Dutta NK (2015) High-speed all-optical encryption and decryption based on two-photon absorption in semiconductor optical amplifiers. IEEE/OSA J Opt Commun Netw 7(4):276–285

    Article  Google Scholar 

  18. Yu CC, Zhou NR, Gong LH, Nie Z (2020) Optical image encryption algorithm based on phase-truncated short-time fractional Fourier transform and hyper-chaotic system. Opt Lasers Eng 124:105816

    Article  Google Scholar 

  19. Wang X, Zhao H, Feng L, Ye X, Zhang H (2019) High-sensitivity image encryption algorithm with random diffusion based on dynamic-coupled map lattices. Opt Lasers Eng 122:225–238

    Article  Google Scholar 

  20. Xingyuan W, Junjian Z, Guanghui C (2019) An image encryption algorithm based on ZigZag transform and LL compound chaotic system. Opt Laser Technol 119

    Google Scholar 

  21. Zhu C, Sun K (2018) Cryptanalyzing and improving a novel color image encryption algorithm using RT-enhanced chaotic tent maps. IEEE Access 6:18759–18770

    Article  Google Scholar 

  22. Zhang X, Wang X (2018) Digital image encryption algorithm based on elliptic curve public cryptosystem. IEEE Access 6:70025–70034

    Article  Google Scholar 

  23. Guan M, Yang X, Hu W (2019) Chaotic image encryption algorithm using frequency-domain DNA encoding. IET Image Proc 13(9):1535–1539

    Article  Google Scholar 

  24. Thoms GRW, Muresan R, Al-Dweik A (2019) Chaotic encryption algorithm with key controlled neural networks for intelligent transportation systems. IEEE Access 7:158697–158709

    Article  Google Scholar 

  25. Nematzadeh H, Enayatifar R, Motameni H, FG, Coelho VN (2018) Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices. Opt Lasers Eng 110:24–32

    Article  Google Scholar 

  26. Rajakumar BR (2013) Impact of static and adaptive mutation techniques on genetic algorithm. Int J Hybrid Intell Syst 10(1):11–22. https://doi.org/10.3233/HIS-120161

    Article  Google Scholar 

  27. Rajakumar BR (2013) Static and adaptive mutation techniques for genetic algorithm: a systematic comparative analysis. Int J Comput Sci Eng 8(2):180–193. https://doi.org/10.1504/IJCSE.2013.053087

    Article  MathSciNet  Google Scholar 

  28. Swamy SM, Rajakumar BR, Valarmathi IR (2013) Design of hybrid wind and photovoltaic power system using opposition-based genetic algorithm with cauchy mutation. In: IET Chennai fourth international conference on sustainable energy and intelligent systems (SEISCON 2013). Chennai, India. https://doi.org/10.1049/ic.2013.0361

  29. George A, Rajakumar BR (2013) APOGA: an adaptive population pool size based genetic algorithm. AASRI Procedia—2013 AASRI conference on intelligent systems and control (ISC 2013), vol 4, pp 288–296. https://doi.org/10.1016/j.aasri.2013.10.043

  30. Rajakumar BR, George A (2012) A new adaptive mutation technique for genetic algorithm. In: proceedings of IEEE international conference on computational intelligence and computing research (ICCIC). Coimbatore, India, pp 1–7. https://doi.org/10.1109/ICCIC.2012.6510293

  31. Mirjalili S, Lewisa A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67

    Article  Google Scholar 

  32. Masadeh R, Mahafzah BA, Sharieh A (2019) Sea lion optimization algorithm. Int J Adv Comput Sci Appl (IJACSA), 10(5)

    Google Scholar 

  33. Koppu S, Viswanatham VM (2018) Medical image security enhancement using two dimensional chaotic mapping optimized by self-adaptive grey wolf algorithm. Evol Intell 11:53–71

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Applications, Jindal College for Women, Bangalore, Karnataka, India

    H. R. Latha

  2. Research Scholar, Hindusthan Institute of Technology & Science, Chennai, India

    H. R. Latha

  3. Department of Computer Applications, Hindustan Institute of Technology & Science, Chennai, India

    A. Ramaprasath

Authors
  1. H. R. Latha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Ramaprasath
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India

    N. R. Shetty

  2. National Institute of Advanced Studies, Bengaluru, Karnataka, India

    L. M. Patnaik

  3. Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India

    H. C. Nagaraj

  4. Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India

    Prasad N. Hamsavath

  5. Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India

    N. Nalini

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Latha, H.R., Ramaprasath, A. (2022). Optimized Two-Dimensional Chaotic Mapping for Enhanced Image Security Using Sea Lion Algorithm. In: Shetty, N.R., Patnaik, L.M., Nagaraj, H.C., Hamsavath, P.N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications. Lecture Notes in Electrical Engineering, vol 790. Springer, Singapore. https://doi.org/10.1007/978-981-16-1342-5_78

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-1342-5_78

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1341-8

  • Online ISBN: 978-981-16-1342-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation