Encryption Algorithms for the Bioinformatics Data
Keywords:
Data Security, Encryption, Cryfa Tools, Forward Algorithm, Biological DataAbstract
Lembar pernyataan
Yth Moderator RINarxiv
Bahwa saya menyatakan:
1) Sebagai penulis artikel berjudul "Encryption Algorithms for the Bioinformatics Data". Melalui surel ini saya menyatakan bahwa artikel ini berstatus (pilih salah satu):
A. Preprint yang telah dikirimkan ke Malaysian Journal of Applied Sciences
2) bahwa artikel ini bukan merupakan karya original. Seandainya di kemudian hari ditemukan ada unsur plagiarisme (sengaja atau tidak sengaja), maka itu adalah tanggung jawab saya dan tim penulis.
Muhammad Aldino Hafidzhah, Arli Aditya Parikesit
---
Abstract
The security of the bioinformatics data is one area that is still overlooked by the cybersecurity community. There are several issues that should be catered accordingly, such as data privacy and restricted data access. Encryption algorithm might be the solution to solve this problem because it is the industry standard approach to the cybersecurity issues. That is why in this review we will try to find the most suitable and effective encryption algorithm that can be used to preserve security to biological data by doing some comparison using several parameters and methods accordingly. It is found that the Cryfa tool is one of the most promising applications for securing the bioinformatics data. Beside the tools, in this regard, artificial intelligence-based approach could leverage the security level significantly.
References
Bernard, S., & Parikesit, A. A. (2020). Artificial Intelligence in Colonoscopy: Improving Medical Diagnostic of Colorectal Cancer. Frontiers in Health Informatics, 9(1), 27. https://doi.org/10.30699/FHI.V9I1.209
Chen, C.-M., Jyan, H.-W., Chien, S.-C., Jen, H.-H., Hsu, C.-Y., Lee, P.-C., … Chan, C.-C. (2020). Containing COVID-19 among 627,386 Persons Contacting with Diamond Princess Cruise Ship Passengers Disembarked in Taiwan: Big Data Analytics. Journal of Medical Internet Research. https://doi.org/10.2196/19540
Fernández-Alemán, J. L., Señor, I. C., Lozoya, P. ángel O., & Toval, A. (2013, June 1). Security and privacy in electronic health records: A systematic literature review. Journal of Biomedical Informatics. Academic Press. https://doi.org/10.1016/j.jbi.2012.12.003
Franz, M., Deiseroth, B., Hamacher, K., Jha, S., Katzenbeisser, S., & Schröder, H. (2012). Towards Secure Bioinformatics Services (Short Paper). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 276–283). https://doi.org/10.1007/978-3-642-27576-0_23
Hasan, M. Z., Mahdi, M. S. R., Sadat, M. N., & Mohammed, N. (2018). Secure count query on encrypted genomic data. Journal of Biomedical Informatics, 81, 41–52. https://doi.org/10.1016/j.jbi.2018.03.003
Hosseini, M., Pratas, D., & Pinho, A. J. (2019). Cryfa: a secure encryption tool for genomic data. Bioinformatics, 35(1), 146–148. https://doi.org/10.1093/bioinformatics/bty645
Kruse, C. S., Frederick, B., Jacobson, T., & Monticone, D. K. (2017, January 1). Cybersecurity in healthcare: A systematic review of modern threats and trends. Technology and Health Care. IOS Press. https://doi.org/10.3233/THC-161263
Kumari, S. (2017). A research Paper on Cryptography Encryption and Compression Techniques. International Journal Of Engineering And Computer Science. https://doi.org/10.18535/ijecs/v6i4.20
Luxton, D. D., Kayl, R. A., & Mishkind, M. C. (2012). MHealth data security: The need for HIPAA-compliant standardization. Telemedicine and E-Health, 18(4), 284–288. https://doi.org/10.1089/tmj.2011.0180
Morel, B. (2011). Artificial intelligence and key to the future of cybersecurity. In Proceedings of the ACM Conference on Computer and Communications Security (pp. 93–97). New York, New York, USA: ACM Press. https://doi.org/10.1145/2046684.2046699
Pratas, D., Hosseini, M., & Pinho, A. J. (2017). Cryfa: A Tool to Compact and Encrypt FASTA Files. In Advances in Intelligent Systems and Computing (pp. 305–312). https://doi.org/10.1007/978-3-319-60816-7_37
Rehman, S. (2016). Characterization of Advanced Encryption Standard (AES) for Textual and Image data. International Journal Of Engineering And Computer Science. https://doi.org/10.18535/ijecs/v5i10.21
Yang Lou, X. (2017). Hidden Markov Model Approaches for Biological Studies. Biometrics & Biostatistics International Journal, 5(4). https://doi.org/10.15406/bbij.2017.05.00139
Zarate, O. A., Brody, J. G., Brown, P., Ramirez-Andreotta, M. D., Perovich, L., & Matz, J. (2016). Balancing Benefits and Risks of Immortal Data: Participants’ Views of Open Consent in the Personal Genome Project. Hastings Center Report, 46(1), 36–45. https://doi.org/10.1002/hast.523
Zhou, X., & Tang, X. (2011). Research and implementation of RSA algorithm for encryption and decryption. In Proceedings of the 6th International Forum on Strategic Technology, IFOST 2011. https://doi.org/10.1109/IFOST.2011.6021216
Downloads
Posted
License
Copyright (c) 2022 Muhammad Aldino Hafidzah, Arli Aditya Parikesit
This work is licensed under a Creative Commons Attribution 4.0 International License.
