Adleman, L. (1994). Molecular computation of solutions to combinatorial problems. Science,266(5187), 1021–1024. https://doi.org/10.1126/science.7973651. https://science.sciencemag.org/content/266/5187/1021.
Barak, B. (2017). The complexity of public-key cryptography (pp. 45–77). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-57048-8_2.
Buchanan, W., & Woodward, A. (2017). Will quantum computers be the end of public key encryption? Journal of Cyber Security Technology, 1(1), 1–22. https://doi.org/10.1080/23742917.2016.1226650.
Buiu, C., & Florea, A. G. (2019). Membrane computing models and robot controller design, current results and challenges. Journal of Membrane Computing, 1(4), 262–269. https://doi.org/10.1007/s41965-019-00029-8.
Fan, S., Paul, P., Wu, T., Rong, H., & Zhang, G. (2020). On applications of Spiking Neural p systems. Applied Sciences, 10(20), 7011. https://doi.org/10.3390/app10207011.
Guo, P., & Xu, W. (2016). A family P system of realizing RSA algorithm. In M. Gong, L. Pan, T. Song, & G. Zhang (Eds.), Bio-inspired computing—theories and applications (pp. 155–167). Singapore: Springer.
Hussain, N., Balamurugan, C., & Mariappan, R. (2015). A novel dna computing based encryption and decryption algorithm. Procedia Computer Science, 46, 463–475. https://doi.org/10.1016/j.procs.2015.02.045.
Ionescu, M., Păun, A., Păun, G., & Pérez-Jiménez, M.J. (2006). Computing with Spiking Neural P systems: Traces and small universal systems. In: Mao C. and Yokomori T. (Eds) DNA Computing. DNA 2006. Lecture Notes in Computer Science. Springer, Berlin, Heidelberg 4287(16), 1–16. https://doi.org/10.1007/11925903_1
Ionescu, M., Păun, G., & Yokomori, T. (2006). Spiking Neural P systems. Fundamenta Informaticae, 71(2), 279–308.
Ishdorj, T. O. (2006). Minimal parallelism for polarizationless P systems. In C. Mao & T. Yokomori (Eds.), DNA Computing (pp. 17–32). Berlin: Springer.
Ishdorj, T. O., & Leporati, A. (2008). Uniform solutions to SAT and 3-SAT by Spiking Neural P systems with pre-computed resources. Natural Computing, 7(4), 519–534. https://doi.org/10.1007/s11047-008-9081-0.
Ishdorj, T.O., Ochirbat, O., & Naimannaran, C. (2020). A \(\mu\)-fluidic biochip design for Spiking Neural P systems. International Journal of Unconventional Computation
Ishdorj, T. O., & Petre, I. (2008). Gene assembly models and boolean circuits. International Journal of Foundations of Computer Science, 19(05), 1133–1145.
Ishdorj, T. O., Petre, I., & Rogojin, V. (2007). Computational power of intramolecular gene assembly. International Journal of Foundations of Computer Science, 18(05), 1123–1136.
Kari, L., & Rozenberg, G. (2008). The many facets of natural computing. Communications of the ACM, 51, 72–83. https://doi.org/10.1145/1400181.1400200.
Karimi, A., & Shahhoseini, H. S. (2012). Cryptanalysis of a substitution-permutation network using gene assembly in ciliates. International Journal of Communications, Network and System Sciences, 5, 154–164.
Liu, Y., Nicolescu, R., & Sun, J. (2020). Formal verification of cP systems using PAT3 and ProB. Journal of Membrane Computing, 2(2), 80–94. https://doi.org/10.1007/s41965-020-00036-0.
Mavroeidis, V., Vishi, K., Zych, M., & Jøsang, A. (2018). The impact of quantum computing on present cryptography. International Journal of Advanced Computer Science and Applications. https://. https://doi.org/10.14569/IJACSA.2018.090354.
Mitrana, V. (2019). Polarization: a new communication protocol in networks of bio-inspired processors. Journal of Membrane Computing, 1(2), 127–143. https://doi.org/10.1007/s41965-018-0001-9.
Narendren., Yathish, Y.B., & Mohan, C. (2018). A cryptosystem using two layers of security-dna and rsa cryptography.
Ochirbat, O., Ishdorj, T. O., & Cichon, G. (2020). An error-tolerant serial binary full-adder via a Spiking Neural P system using HP/LP basic neurons. Journal of Membrane Computing, 2(1), 42–48. https://doi.org/10.1007/s41965-020-00033-3.
Păun, G. (2002). Membrane computing: an introduction. Berlin: Springer-Verlag.
Rivest, R., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21, 120–126.
Shor, P. W. (1997). Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Journal on Computing, 26(5), 1484–1509. https://doi.org/10.1137/S0097539795293172.
Wang, H., Zhou, K., Zhang, G., Paul, P., Duan, Y., Qi, H., & Rong, H. (2020). Application of weighted Spiking Neural P systems with rules on synapses for breaking RSA encryption. International Journal of Unconventional Computing, 15, 37–58.
Wang, X., & Zhang, Q. (2009). DNA computing-based cryptography. In: 2009 Fourth International on Conference on Bio-Inspired Computing, pp. 1–3.
Weng-Long, C., Lin, K., Chen, J. C., Chih-Chiang, W., Lai, L., Guo, M., & Michael, H. (2011). molecular solutions of the RSA public-key cryptosystem on a DNA-based computer. The Journal of Supercomputing - TJS, 61, 1–31. https://doi.org/10.1007/s11227-011-0627-z.
Weste, N. H. E., & Eshraghian, K. (1985). Principles of CMOS VLSI design: a systems perspective. Boston: Addison-Wesley Longman Publishing Co. Inc.
Xie, H., Li, B., Qin, J., Huang, Z., Zhu, Y., & Lin, B. (2009). A splicing model based DNA computing approach on microfluidic chip. Electrophoresis, 30(20), 3514–3518. https://doi.org/10.1002/elps.200900323.
Xu, Z., Cavaliere, M., An, P., Vrudhula, S., & Cao, Y. (2014). The stochastic loss of spikes in Spiking Neural P systems: Design and implementation of reliable arithmetic circuits. Fundamenta Informaticae, 134(1–2), 183–200. https://doi.org/10.3233/FI-2014-1098.
Zhang, G., Shang, Z., Verlan, S., Martínez-del Amor, M. A., Yuan, C., Valencia-Cabrera, L., & Pérez-Jiménez, M. J. (2020). An overview of hardware implementation of membrane computing models. ACM Computing Surveys. https://doi.org/10.1145/3402456.