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2000
Volume 18, Issue 8
  • ISSN: 2666-2558
  • E-ISSN: 2666-2566

Abstract

Background

Indoor space layout planning and design involves sensitive and confidential information. To enhance the security and confidentiality of such data, the study introduces an advanced image encryption algorithm. This algorithm is based on simultaneous chaotic systems and bit plane permutation diffusion, aiming to provide a more secure and reliable approach to indoor space layout design.

Methods

The study proposes an image encryption algorithm that incorporates simultaneous chaotic systems and bit plane permutation diffusion. This algorithm is then applied to the process of indoor space layout planning and design. Comparative analysis is conducted to evaluate the performance of the proposed algorithm against other existing methods. Additionally, a comparative testing of indoor space layout planning and design methods is carried out to assess the overall effectiveness of the research method.

Results

Through the algorithm comparison test, information entropy, adjacent pixel distribution and response time were selected as evaluation indexes. The results demonstrated that the improved image encryption algorithm exhibited superior performance in terms of information entropy (with average information entropy of 7.9990), anti-noise attack capability (with PSNR value of 37.58db), and anti-differential attack capability (with NPCR and UACI values of 99.6% and 33.5%) when compared to the benchmark algorithm. In the actual application effect test, the study selected space utilization, functionality, security, ease of use, confidentiality, flexibility and other evaluation indicators. A comparative analysis of the actual application effects of various interior design projects revealed that the interior space layout planning and design method proposed in the study exhibited notable superiority over the comparison method across all indicators. In particular, it showed overall advantages in space utilization (92.5% in modern apartment design), functionality score (9.5 in future living experience museum design), and safety assessment.

Conclusion

The above key results demonstrate that the improved image encryption algorithm and the designed indoor space layout planning method have substantial practical applications and are expected to enhance security and confidentiality in the field of indoor space layout planning, thereby providing users with a more optimal experience.

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2024-12-30
2025-11-01
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References

  1. GuoY. MustafaogluZ. KoundalD. Spam detection using bidirectional transformers and machine learning classifier algorithms.JCCE2022215910.47852/bonviewJCCE2202192
    [Google Scholar]
  2. ItamiH. PengB. KojimaT. Comparative analysis: Cognitive process of residential interior space: Interior planning method from Professional and Non-Professional point of view - Part IJEE (Transactions of AIJ)20198475612713410.3130/aije.84.127
    [Google Scholar]
  3. FangY. LuoB. ZhaoT. HeD. JiangB. LiuQ. ST‐SIGMA: Spatio-temporal semantics and interaction graph aggregation for multi-agent perception and trajectory forecasting.CAAI Trans. Intell. Technol.20227474475710.1049/cit2.12145
    [Google Scholar]
  4. C CA. Optimal facility layout planning for AGV-based modular prefabricated manufacturing system.Autom. Construct.2019987310321
    [Google Scholar]
  5. WangX. QuZ. SongX. LiH. PanZ. Using taxi GPS trajectory data to optimize the spatial layout of urban taxi stands.Transp. Res. Rec.20212675330131210.1177/0361198120970537
    [Google Scholar]
  6. JiangD. LiuL. WangX. RongX. Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial.IET Image Process.202115143698371710.1049/ipr2.12237
    [Google Scholar]
  7. ShengY. LiJ. DiX. ManZ. LiuZ. Bit‐level image encryption algorithm based on fully‐connected‐like network and random modification of edge pixels.IET Image Process.202216102769279010.1049/ipr2.12525
    [Google Scholar]
  8. ZhangQ. HanJ. YeY. Multi‐image encryption algorithm based on image hash, bit‐plane decomposition and dynamic DNA coding.IET Image Process.202115488589610.1049/ipr2.12069
    [Google Scholar]
  9. XingY.W. SuoG. Image encryption algorithm for synchronously updating Boolean networks based on matrix semi-tensor product theory.Inf. Sci.202050751636
    [Google Scholar]
  10. XuJ. MouJ. LiuJ. HaoJ. The image compression–encryption algorithm based on the compression sensing and fractional-order chaotic system.Vis. Comput.20223851509152610.1007/s00371‑021‑02085‑7
    [Google Scholar]
  11. HuangX. DongY. YeG. YapW.S. GoiB.M. Visually meaningful image encryption algorithm based on digital signature.Digit. Commun. Netw.20239115916510.1016/j.dcan.2022.04.028
    [Google Scholar]
  12. GaoX. MouJ. BanerjeeS. CaoY. XiongL. ChenX. An effective multiple-image encryption algorithm based on 3D cube and hyperchaotic mapJ. King Saud Univ. - Comput. Inf. Sci.20223441535155110.1016/j.jksuci.2022.01.017
    [Google Scholar]
  13. ChoJ.Y. SuhJ. The architecture and interior design domain–specific spatial ability test (AISAT): Its validity and reliability.J. Inter. Design2022472113010.1111/joid.12211
    [Google Scholar]
  14. YuanJ. CaoY. KangY. SongW. YinZ. BaR. MaQ. 3D Layout encoding network for spatial‐aware 3D saliency modelling.IET Comput. Vis.201913548048810.1049/iet‑cvi.2018.5591
    [Google Scholar]
  15. LiX. ZhangL. LiuS. WangH. Multi-objective optimization of indoor space layout design based on genetic algorithm.J. Build. Perform. Simul.2020133281296
    [Google Scholar]
  16. Mousavi AslS.R. SafariH. Evaluation of daylight distribution and space visual quality at medical centers through spatial layout.J. Asian Archit. Build. Eng.202120551251910.1080/13467581.2020.1800476
    [Google Scholar]
  17. WangY. ZhangH. LiangL. YangY. Deep learning-based indoor space layout design method.IEEE Access202196148975148986
    [Google Scholar]
  18. ZhangQ. HanJ. YeY. Image encryption algorithm based on image hashing, improved chaotic mapping and DNA coding.IET Image Process.201913142905291510.1049/iet‑ipr.2019.0667
    [Google Scholar]
  19. SamehS.M. MoustafaH.E.D. AbdelHayE.H. AtaM.M. An effective chaotic maps image encryption based on metaheuristic optimizers.J. Supercomput.202480114120110.1007/s11227‑023‑05413‑x
    [Google Scholar]
  20. ZhouC. Digital architectural decoration design and production based on computer image.Int. J. Data Min. Bioinform.2024283/420121810.1504/IJDMB.2024.139446
    [Google Scholar]
  21. HongW.C. LiM.W. GengJ. ZhangY. Novel chaotic bat algorithm for forecasting complex motion of floating platforms.Appl. Math. Model.201972842544310.1016/j.apm.2019.03.031
    [Google Scholar]
  22. KA. User name-based compression and encryption of images using chaotic compressive sensing theory.Comput. J.202467130432210.1093/comjnl/bxac175
    [Google Scholar]
  23. ShenD. QianJ. WangG. JiaoY. JiaoY. ZhaoQ. Tunable color generation in CdTe-doped silicate glass enabled by ultrashort laser pulses: Interior coloring and multilevel encryption.Opt. Express20223015273952740610.1364/OE.462809 36236911
    [Google Scholar]
  24. TengL. WangX. XianY. Image encryption algorithm based on a 2D-CLSS hyperchaotic map using simultaneous permutation and diffusion.Inf. Sci.20226059718510.1016/j.ins.2022.05.032
    [Google Scholar]
  25. LiM. LuD. XiangY. ZhangY. RenH. Cryptanalysis and improvement in a chaotic image cipher using two-round permutation and diffusion.Nonlinear Dyn.2019961314710.1007/s11071‑019‑04771‑7
    [Google Scholar]
  26. WangJ. LiS.C. LinP.C. A psychophysical and questionnaire investigation on the spatial disorientation triggered by cockpit layout and design.Int. J. Ind. Ergon.201972334735310.1016/j.ergon.2019.06.008
    [Google Scholar]
  27. KhanS. NikM.A. FayazbakhshK. FawazZ. Continuous curvilinear variable stiffness design for improved strength of a panel with a cutout.Mech. Adv. Mater. Structures2020295975983
    [Google Scholar]
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