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Biocyber Interface-Based Privacy for Internet of Bio-nano Things

Wireless Personal Communications volume 114, pages 1465–1483 (2020)Cite this article

Abstract

The concept of Internet of bio-nano thing (IoBNT) arose from the need for Biological nanomachines to interconnect intra-body nanonetwork with the cyber Internet aiming to exchange information. However, while numerous studies have focused on communication efficiency among the nanodevices in a given network, challenges such as the IoBNT security, and the interface connection between the nanonetwork and the Internet are yet to be addressed. Thus, in this study, we propose a privacy scheme working on the top of the biocyber interface in the IoBNT paradigm. The proposed chaotic-system is based on the command signal coming from medical personnel to biocyber device embedded on the human body wherein a masked version of feature generated by applying modified Logistic map for increasing the privacy of the human life and released the exact dose. Additionally, the proposed scheme includes BPSK modulation and feature extraction with zero crossing rate. Finally, the privacy scheme increases the key space, thereby ensuring that the right dose is released and the privacy of human life is achieved. The performance analysis of the proposed scheme is presented firstly, by evaluating the proposed privacy scheme working on the top of biocyber interface device by using receiver operating characteristics curve and bit error rate. Then, we study the performance proposed scheme by employing the compartmental models in the forward and reverse biocyber interface of the IoBNT paradigm. The simulation results of the developed model reveal that the proposed IoBNT-based the privacy scheme can enhance the delivery of therapeutic drugs to the target cells while maximizing the privacy issues.

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References

  1. Chude-Okonkwo, U. A., Malekian, R., & Maharaj, B. S. (2016). Molecular communication model for targeted drug delivery in multiple disease sites with diversely expressed enzymes. IEEE Transactions on Nanobioscience, 15(3), 230–245.

    Google Scholar 

  2. Chude-Okonkwo, U. A., et al. (2015). Bio-inspired approach for eliminating redundant nanodevices in internet of bio-nano things. In 2015 IEEE Globecom workshops (GC Wkshps). 2015. IEEE.

  3. Akyildiz, I. F., Brunetti, F., & Blázquez, C. (2008). Nanonetworks: A new communication paradigm. Computer Networks, 52(12), 2260–2279.

    Google Scholar 

  4. Freitas, R. A. (2005). Current status of nanomedicine and medical nanorobotics. Journal of Computational and Theoretical Nanoscience, 2(1), 1–25.

    Google Scholar 

  5. Griffith, L. G., & Naughton, G. (2002). Tissue engineering–current challenges and expanding opportunities. Science, 295(5557), 1009–1014.

    Google Scholar 

  6. Byrne, R., & Diamond, D. (2006). Chemo/bio-sensor networks. Nature Materials, 5(6), 421.

    Google Scholar 

  7. Akyildiz, I. F., et al. (2015). The internet of bio-nano things. IEEE Communications Magazine, 53(3), 32–40.

    Google Scholar 

  8. Cascone, S., et al. (2013). Pharmacokinetics of Remifentanil: A three-compartmental modeling approach. Translational medicine@ UniSa (Vol. 7, pp. 18).

  9. Atakan, B., Akan, O. B., & Balasubramaniam, S. (2012). Body area nanonetworks with molecular communications in nanomedicine. IEEE Communications Magazine, 50(1), 28–34.

    Google Scholar 

  10. Youssef, C., et al. (2013). A molecular communication system model for particulate drug delivery systems. IEEE Transactions on Biomedical Engineering, 60(12), 3468–3483.

    Google Scholar 

  11. Nel, A. E., et al. (2009). Understanding biophysicochemical interactions at the nano-bio interface. Nature Materials, 8(7), 543.

    Google Scholar 

  12. Nakano, T., et al. (2012). Swarming biological nanomachines through molecular communication for targeted drug delivery. In Proceedings SCIS-ISIS.

  13. Nakano, T., et al. (2014). Molecular communication among biological nanomachines: A layered architecture and research issues. IEEE Transactions on Nanobioscience, 13(3), 169–197.

    Google Scholar 

  14. Felicetti, L., et al. (2016). Applications of molecular communications to medicine: A survey. Nano Communication Networks, 7, 27–45.

    Google Scholar 

  15. Pattni, B. S., Chupin, V. V., & Torchilin, V. P. (2015). New developments in liposomal drug delivery. Chemical Reviews, 115(19), 10938–10966.

    Google Scholar 

  16. Daraee, H., et al. (2016). Application of liposomes in medicine and drug delivery. Artificial Cells, Nanomedicine, and Biotechnology, 44(1), 381–391.

    Google Scholar 

  17. Liu, D., et al. (2016). The smart drug delivery system and its clinical potential. Theranostics, 6(9), 1306.

    Google Scholar 

  18. Dollard, M.-A., & Billard, P. (2003). Whole-cell bacterial sensors for the monitoring of phosphate bioavailability. Journal of Microbiological Methods, 55(1), 221–229.

    Google Scholar 

  19. Monson, E., et al. (2003). PEBBLE nanosensors for in vitro bioanalysis. Biomedical Photonics Handbook, 9, 1–14.

    Google Scholar 

  20. Dhillon, S., & Kostrzewski, A. (2006). Clinical pharmacokinetics. London: Pharmaceutical Press.

    Google Scholar 

  21. ShahMohammadian, H., Messier, G. G., & Magierowski, S. (2012). Optimum receiver for molecule shift keying modulation in diffusion-based molecular communication channels. Nano Communication Networks, 3(3), 183–195.

    Google Scholar 

  22. Klein, B. G. (2019). Cunningham’s textbook of veterinary physiology. Amsterdam: Elsevier Health Sciences.

    Google Scholar 

  23. El-Hoseny, H., et al. (2014). Digital image encryption in transform domains. Menof: Faculty of Electronic Engineering, Menofia University.

    Google Scholar 

  24. Ramadan, N., et al. (2017). Permutation-substitution image encryption scheme based on a modified chaotic map in transform domain. Journal of Central South University, 24(9), 2049–2057.

    Google Scholar 

  25. Wang, X., et al. (2018). Bacterial luciferase gene cassette as a real-time bioreporter for infection model and drug evaluation. Current Pharmaceutical Design, 24(8), 952–958.

    Google Scholar 

  26. Close, D. M., et al. (2011). Light without substrate amendment: The bacterial luciferase gene cassette as a mammalian bioreporter. In Sensing technologies for global health, military medicine, disaster response, and environmental monitoring; and biometric technology for human identification VIII. 2011. International Society for Optics and Photonics.

  27. Di Paolo, D., et al. (2008). Drug delivery systems: Application of liposomal anti-tumor agents to neuroectodermal cancer treatment. Tumori Journal, 94(2), 246–253.

    Google Scholar 

  28. Bozzuto, G., & Molinari, A. (2015). Liposomes as nanomedical devices. International Journal of Nanomedicine, 10, 975.

    Google Scholar 

  29. El-atty, S. M. A., El-Taweel, A., & El-Rabaie, S. (2018). Transmission of nanoscale information-based neural communication-aware ligand–receptor interactions. Neural Computing and Applications, 30(11), 3509–3522.

    Google Scholar 

  30. Bonate, P. (2001). Advanced methods of pharmacokinetic and pharmacodynamic systems analysis. IDrugs: The Investigational Drugs Journal, 4(9), 1017–1020.

    Google Scholar 

  31. Chude-Okonkwo, U. A., Malekian, R., & Maharaj, B. (2016). Biologically inspired bio-cyber interface architecture and model for internet of bio-nanothings applications. IEEE Transactions on Communications, 64(8), 3444–3455.

    Google Scholar 

  32. Gutierrez, P. S., Monteoliva, D., & Diambra, L. (2012). Cooperative binding of transcription factors promotes bimodal gene expression response. PLoS ONE, 7(9), e44812.

    Google Scholar 

  33. Sherwood, A. V., & Henkin, T. M. (2016). Riboswitch-mediated gene regulation: Novel RNA architectures dictate gene expression responses. Annual Review of Microbiology, 70, 361–374.

    Google Scholar 

  34. Yagil, G., & Yagil, E. (1971). On the relation between effector concentration and the rate of induced enzyme synthesis. Biophysical Journal, 11(1), 11–27.

    Google Scholar 

  35. Vijayaraghavan, R., et al. (2007). A bioreporter bioluminescent integrated circuit for very low-level chemical sensing in both gas and liquid environments. Sensors and Actuators B: Chemical, 123(2), 922–928.

    Google Scholar 

  36. Muschelli, J. (2019). ROC and AUC with a binary predictor: A potentially misleading metric. arXiv:1903.04881.

  37. Matyka, M., Khalili, A., & Koza, Z. (2008). Tortuosity-porosity relation in porous media flow. Physical Review E, 78(2), 026306.

    Google Scholar 

  38. Chahibi, Y., et al. (2015). Molecular communication modeling of antibody-mediated drug delivery systems. IEEE Transactions on Biomedical Engineering, 62(7), 1683–1695.

    Google Scholar 

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology (HIT), Harbin, China

    Aya El-Fatyany, Hongzhi Wang & Mehak Khan

  2. Department of Mathematics, Faculty of Science, Menoufia University, Shebin El-Kom, Egypt

    Aya El-Fatyany

  3. Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

    Saied M. Abd El-atty

Authors
  1. Aya El-Fatyany
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  2. Hongzhi Wang
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  3. Saied M. Abd El-atty
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  4. Mehak Khan
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Correspondence to Aya El-Fatyany.

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El-Fatyany, A., Wang, H., Abd El-atty, S.M. et al. Biocyber Interface-Based Privacy for Internet of Bio-nano Things. Wireless Pers Commun 114, 1465–1483 (2020). https://doi.org/10.1007/s11277-020-07433-9

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  • DOI: https://doi.org/10.1007/s11277-020-07433-9

Keywords

  • Wireless body area network
  • Nanotechnology
  • Internet of bio-nano things
  • Nanosensors
  • Target drug delivery
  • Molecular communication