Skip to main content
SpringerLink
Log in

Efficient protection using chaos for Context-Adaptive Binary Arithmetic Coding in H.264/Advanced Video Coding

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Recently, video encryption has been widely investigated to enhance the protection for video data, yet the encryption efficiency may not be considered sufficiently so that some encryption schemes are unsuitable for the real-time applications. In this paper, we propose a novel chaotic selective encryption scheme (CSES) based on Context-Adaptive Binary Arithmetic Coding (CABAC) of H.264/Advanced Video Coding (H.264/AVC) for the practical applications. To satisfy the secure and real-time requirement, we select the important and sensitive encryption objects on the basis of the analysis of syntax elements in CABAC. According to the characteristics of chosen syntax elements, two encryption methods combined with two designed chaos-based key stream generators (KSGs) are presented in CSES to implement the video encryption with the reasonable and acceptable compression and encryption performance. The experimental results and security analysis demonstrate that the proposed CSES with the format-compliance has the good confidentiality and can resist some common security attacks, such as the brute force attack, histogram attack, information entropy attack, replacement attack and some other common attacks. It can be found from the comparison experiments about the encryption efficiency that our CSES has the higher real-time performance. The comparison analysis with other video encryption methods illustrates that the proposed CSES is more suitable for the practical applications.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Abomhara M, Zakaria O, Khalifa OO et al (2010) Enhancing selective encryption for H. 264/AVC using advance encryption standard. Int J Comput Theory Eng 2(2):223–229

    Google Scholar 

  2. Alassaf N, Alkazemi B, Gutub A (2017) Applicable light-weight cryptography to secure medical data in IoT systems. J Res Eng Appl Sci 2(2):50–58

    Google Scholar 

  3. Al-Azawi MKM, Gaze AM (2018) Combined speech compression and encryption using chaotic compressive sensing with large key size. IET Sign Proc 12(2):214–218

    Article  Google Scholar 

  4. Aljuaid N, Gutub A, Khan E (2014) Stego-system for hiding text in images of personal computers. In: Proceedings of 2014 International Conference on Advanced Engineering Technologies, AET-2014, Dubai UAE, pp 250–256

  5. Al-Juaid NA, Gutub AA, Khan EA (2018) Enhancing PC data security via combining RSA cryptography and video based steganography. J Inform Sec Cyber Res 1(1):8–18

    Google Scholar 

  6. Asghar MN, Ghanbari M (2013) An efficient security system for CABAC bin-strings of H.264/SVC. IEEE Trans Circ Syst Video Technol 23(3):425–437

    Article  Google Scholar 

  7. Asghar MN, Ghanbari M, Fleury M et al (2015) Sufficient encryption based on entropy coding syntax elements of H.264/SVC. Multimed Tools Appl 74(23):10215–10241

    Article  Google Scholar 

  8. Chiaraluce F, Ciccarelli L, Gambi E, Pierleoni P, Reginelli M (2002) A new chaotic algorithm for video encryption. IEEE Trans Consum Electron 48(4):838–844

    Article  Google Scholar 

  9. Ding X, Deng Y, Yang G et al (2017) Design of new scan orders for perceptual encryption of H.264/AVC videos. IET Inf Secur 11(2):55–65

    Article  Google Scholar 

  10. Elhoseny M, Elminir H, Riad A et al (2016) A secure data routing schema for WSN using Elliptic Curve Cryptography and homomorphic encryption. J King Saud Univ - Comput Inform Sci 28(3):262–275

    Google Scholar 

  11. Elhoseny M, Yuan X, ElMinir HK, Riad AM (2016) An energy efficient encryption method for secure dynamic WSN. Sec Commun Netw 9(13):2024–2031

    Google Scholar 

  12. Fan Y, Wang J, Ikenaga T et al (2007) A new video encryption scheme for H.264/AVC. In: Proceedings of the multimedia 8th Pacific rim conference on advances in multimedia information processing. Springer-Verlag, Berlin, pp 246–255

    Google Scholar 

  13. Ghouti L (2012) Method of performing cipher block chaining using elliptic polynomial cryptography. Patent Application Publication, United States, pp 1–37

    Google Scholar 

  14. Gutub AA (2011) Subthreshold SRAM designs for cryptography security computations. Software Engineering and Computer Systems, Springer Berlin Heidelberg. 104–110

  15. Gutub A, AI-Juaid N (2018) Multi-bits stego-system for hiding text in multimedia images based on user security priority. J Comput Hardw Eng 1(2):1–9

    Google Scholar 

  16. Gutub AA, Khan EA (2011) Using subthreshold SRAM to design low-power crypto hardware. Int J New Comput Architect Appl 1(2):474–483

    Google Scholar 

  17. Gutub AA, Khan AA (2013) Hybrid crypto hardware utilizing symmetric-key and public-key cryptosystems. In: International conference on advanced computer science applications and technologies. IEEE:116–121. https://doi.org/10.1109/ACSAT.2012.44

  18. Gutub A, Al-Juaid N, Khan E (2017) Counting-based secret sharing technique for multimedia applications. Multimed Tools Appl 1–29. https://doi.org/10.1007/s11042-017-5293-6

  19. Hamza R (2017) A novel pseudo random sequence generator for image-cryptographic applications. J Inform Sec Appl 35:119–127

    Google Scholar 

  20. Hamza R, Titouna F (2016) A novel sensitive image encryption algorithm based on the Zaslavsky chaotic map. Inf Syst Secur 25(4–6):162–179

    Google Scholar 

  21. Hermassi H, Hamdi M, Rhouma R, Belghith SM (2017) A joint encryption-compression codec for speech signals using the ITU-T G.711 standard and chaotic map. Multimed Tools Appl 76(1):1177–1200

    Article  Google Scholar 

  22. Huang YW, Hsieh BY, Chen TC, Chen LG (2005) Analysis, fast algorithm, and VLSI architecture design for H.264/AVC intra frame coder. IEEE Trans Circ Syst Video Technol 15(3):378–401

    Article  Google Scholar 

  23. Huynh-Thu Q, Ghanbari M (2012) The accuracy of PSNR in predicting video quality for different video scenes and frame rates. Telecommun Syst 49(1):35–48

    Article  Google Scholar 

  24. Joshi JM, Dalal UD (2016) Highly secure and fast video encryption using minimum overhead in H.264/AVC bitstream. J Test Eval 44(4):1461–1472

    Article  Google Scholar 

  25. Khlif N, Damak T, Kammoun F et al (2014) A very efficient encryption scheme for the H.264/AVC CODEC adopted in Intra prediction mode. In: Image processing applications and systems conference. IEEE:1–7. https://doi.org/10.1109/IPAS.2014.7043256

  26. Khlif N, Damak T, Kammoun F, Masmoudi N (2016) Joint selective encryption of CAVLC and signs of motion vectors for H.264/AVC. J Test Eval 44(1):160–174

    Article  Google Scholar 

  27. Khlif N, Masmoudi A, Kammoun F, Masmoudi N (2018) Secure chaotic dual encryption scheme for H.264/AVC video conferencing protection. IET Image Process 12(1):42–52

    Article  Google Scholar 

  28. Li S, Chen G, Mou X (2005) On the dynamical degradation of digital piecewise linear chaotic maps. Int J Bifurcation Chaos 15(10):3119–3151

    Article  MathSciNet  MATH  Google Scholar 

  29. Lian S, Liu Z, Ren Z, Wang H (2006) Secure advanced video coding based on selective encryption algorithms. IEEE Trans Consum Electron 52(2):621–629

    Article  Google Scholar 

  30. Maniccam SS, Bourbakis NG (2004) Image and video encryption using SCAN patterns. Pattern Recognition 37(4):725–737

    Article  Google Scholar 

  31. Marpe D, Schwarz H, Wiegand T (2003) Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard. IEEE Trans Circ Syst Video Technol 13(7):620–636

    Article  Google Scholar 

  32. Muhammad K, Hamza R, Ahmad J et al (2018) Secure surveillance framework for IoT systems using probabilistic image encryption. IEEE Trans Indust Inform 14(8):3679–3689

    Article  Google Scholar 

  33. Parvez MT, Adnan A, Gutub AA (2011) Vibrant color image steganography using channel differences and secret data distribution. Kuwait J Ofence Eng 38:127–142

    Google Scholar 

  34. Peng F, Zhu XW, Long M (2013) An ROI privacy protection scheme for H.264 video based on FMO and chaos. IEEE Trans Inform Foren Sec 8(10):1688–1699

    Article  Google Scholar 

  35. Peng F, Gong X, Long M, Sun X (2017) A selective encryption scheme for protecting H.264/AVC video in multimedia social network. Multimed Tools Appl 76(3):3235–3253

    Article  Google Scholar 

  36. Podesser M, Schmidt H, Uhl A (2002) Selective bitplane encryption for secure transmission of image data in mobile environments. In: Proceedings of the 5th IEEE Nordic signal processing symposium (NORSIG 2002). Tromso-Trondheim, Norway, pp 4–6

    Google Scholar 

  37. Puri A, Chen X, Luthra A (2004) Video coding using the H.264/MPEG-4 AVC compression standard. Signal Process Image Commun 19(9):793–849

    Article  Google Scholar 

  38. Sallam AI, El-Rabaie ESM, Faragallah OS (2018) CABAC-based selective encryption for HEVC using RC6 in different operation modes. Multimed Tools Appl 77(21):28395–28416

    Article  Google Scholar 

  39. Sallam AI, Faragallah OS, El-Rabaie ESM (2018) HEVC selective encryption using RC6 block cipher technique. IEEE Trans Multimed 20(7):1636–1644

    Article  Google Scholar 

  40. Shahid Z, Puech W (2013) Visual protection of HEVC video by selective encryption of CABAC binstrings. IEEE Trans Multimed 16(1):24–36

    Article  Google Scholar 

  41. Shahid Z, Chaumont M, Puech W (2011) Fast protection of H.264/AVC by selective encryption of CAVLC and CABAC for I and P frames. IEEE Trans Circ Syst Video Technol 21(5):565–576

    Article  Google Scholar 

  42. Shehab A, Elhoseny M, Muhammad K et al (2018) Secure and robust fragile watermarking scheme for medical images. IEEE Acc 6:10269–10278

    Article  Google Scholar 

  43. Shen H, Zhuo L, Zhao Y (2014) An efficient motion reference structure based selective encryption algorithm for H.264 videos. IET Inf Secur 8(3):199–206

    Article  Google Scholar 

  44. Thakur S, Singh AK, Ghrera SP et al (2018) Multi-layer security of medical data through watermarking and chaotic encryption for tele-health applications. Multimed Tools Appl 2:1–14

    Google Scholar 

  45. Tong X, Zhang M, Wang Z, Ma J (2016) A joint color image encryption and compression scheme based on hyper-chaotic system. Nonlinear Dynam 84(4):2333–2356

    Article  Google Scholar 

  46. Tong X, Chen P, Zhang M (2017) A joint image lossless compression and encryption method based on chaotic map. Multimed Tools Appl 76(12):13995–14020

    Article  Google Scholar 

  47. Varalakshmi LM, Sudha GF, Jaikishan G (2014) A selective encryption and energy efficient clustering scheme for video streaming in wireless sensor networks. Telecommun Syst 56(3):357–365

    Article  Google Scholar 

  48. Wallendael GV, Boho A, Cock JD et al (2013) Encryption for high efficiency video coding with video adaptation capabilities. IEEE Trans Consum Electron 59(3):634–642

    Article  Google Scholar 

  49. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612

    Article  Google Scholar 

  50. Wang Y, O’Neill M, Kurugollu F (2013) A tunable encryption scheme and analysis of fast selective encryption for CAVLC and CABAC in H.264/AVC. IEEE Trans Circ Syst Video Technol 23(9):1476–1490

    Article  Google Scholar 

  51. Wiegand T, Sullivan GJ, Bjontegaard G, Luthra A (2003) Overview of the H.264/AVC video coding standard. IEEE Trans Circ Syst Video Technol 13(7):560–576

    Article  Google Scholar 

  52. Xu H, Tong XJ, Zhang M, Wang Z, Li L (2016) Dynamic video encryption algorithm for H.264/AVC based on a spatiotemporal chaos system. J Opt Soc Am A 33(6):1166–1174

    Article  Google Scholar 

  53. Zhang Y, Zhou J, Chen F et al (2016) A block compressive sensing based scalable encryption framework for protecting significant image regions. Int J Bifurcation Chaos 26(11):1234–1247

    MATH  Google Scholar 

  54. Zhang Y, Zhou J, Chen F et al (2016) Embedding cryptographic features in compressive sensing. Neurocomputing 205:472–480

    Article  Google Scholar 

  55. Zhou N, Yang J, Tan C et al (2015) Double-image encryption scheme combining DWT-based compressive sensing with discrete fractional random transform. Opt Commun 354:112–121

    Article  Google Scholar 

  56. Zhou N, Li H, Wang D et al (2015) Image compression and encryption scheme based on 2D compressive sensing and fractional Mellin transform. Opt Commun 343:10–21

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant numbers 61374178, 61402092, 61603182]; the Online Education Research Fund of the MOE Research Center for Online Education, China [qtone education, grant number 2016ZD306]; the Ph.D. Start-Up Foundation of Liaoning Province, China [grant number 201501141]; and the Fundamental Research Funds for the Central Universities [grant number N171704004].

Author information

Authors and Affiliations

  1. Software College, Northeastern University, Shenyang, 110819, China

    Yanjie Song, Zhiliang Zhu, Wei Zhang & Hai Yu

Authors
  1. Yanjie Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhiliang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hai Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhiliang Zhu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

All the authors have been informed about this submission.

This research does not involve any animals.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, Y., Zhu, Z., Zhang, W. et al. Efficient protection using chaos for Context-Adaptive Binary Arithmetic Coding in H.264/Advanced Video Coding. Multimed Tools Appl 78, 18967–18994 (2019). https://doi.org/10.1007/s11042-019-7253-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7253-9

Keywords

Search

Navigation