With over 10 million points of genetic variation from person to person, every individual’s genome is unique and provides a highly reliable form of identification. This is because the genetic code is specific to each individual and does not change over time. Genetic information has been used to identify individuals in a variety of contexts, such as criminal investigations, paternity tests, and medical research. In this study, each individual’s genetic makeup has been formatted to create a secure, unique code that incorporates various elements, such as species, gender, and the genetic identification code itself. The combinations of markers required for this code have been derived from common single nucleotide polymorphisms (SNPs), points of variation found in the human genome. The final output is in the form of a 24 numerical code with each number having three possible combinations. The custom code can then be utilized to create various modes of identification on the decentralized blockchain network as well as personalized services and products that offer users a novel way to uniquely identify themselves in ways that were not possible before.
References
[1]
Madakam, S., et al. (2015) Internet of Things (IoT): A Literature Review. Journal of Computer and Communications, 3, 164-173. https://doi.org/10.4236/jcc.2015.35021
[2]
Gaudet, M., et al. (2009) Allele-Specific PCR in SNP Genotyping. In: Komar, A., Ed., Single Nucleotide Polymorphisms. Methods in Molecular Biology, Humana Press, Totowa, NJ, 415-424. https://doi.org/10.1007/978-1-60327-411-1_26
[3]
Su, W., et al. (2020) Do Men Become Addicted to Internet Gaming and Women to Social Media? A Meta-Analysis Examining Gender-Related Differences in Specific Internet Addiction. Computers in Human Behavior, 113, Article ID: 106480. https://doi.org/10.1016/j.chb.2020.106480
[4]
Mystakidis, S. (2022) Metaverse. Encyclopedia, 2, 486-497. https://doi.org/10.3390/encyclopedia2010031
[5]
Ives, B., Walsh, K.R. and Schneider, H. (2004) The Domino Effect of Password Reuse. Communications of the ACM, 47, 75-78. https://doi.org/10.1145/975817.975820
[6]
Alabdan, R. (2020) Phishing Attacks Survey: Types, Vectors, and Technical Approaches. Future Internet, 12, Article 168. https://doi.org/10.3390/fi12100168
[7]
Wright, E. (2018) The Future of Facial Recognition Is Not Fully Known: Developing Privacy and Security Regulatory Mechanisms for Facial Recognition in the Retail Sector. The Fordham Intellectual Property, Media and Entertainment Law Journal, 29, Article 611.
[8]
Chen, J., Lv, Z. and Song, H. (2019) Design of Personnel Big Data Management System Based on Blockchain. Future Generation Computer Systems, 101, 1122-1129. https://doi.org/10.1016/j.future.2019.07.037
[9]
Chowdhury, M.U., et al. (2021) Blockchain Application in Banking System. Journal of Software Engineering and Applications, 14, 298-311. https://doi.org/10.4236/jsea.2021.147018
[10]
Allison, A., et al. (2005) Digital Identity Matters. Journal of the American Society for Information Science and Technology, 56, 364-372. https://doi.org/10.1002/asi.20112
[11]
Argento, L., et al. (2020) ID-Service: A Blockchain-Based Platform to Support Digital-Identity-Aware Service Accountability. Applied Sciences, 11, Article 165. https://doi.org/10.3390/app11010165
[12]
Sule, M.J., Zennaro, M. and Thomas, G. (2021) Cybersecurity through the Lens of Digital Identity and Data Protection: Issues and Trends. Technology in Society, 67, Article ID: 101734. https://doi.org/10.1016/j.techsoc.2021.101734
[13]
Buckingham, D. (2008) Introducing Identity. MacArthur Foundation Digital Media and Learning Initiative.
[14]
Schwartz, P.M. and Solove, D.J. (2011) The PII Problem: Privacy and a New Concept of Personally Identifiable Information. New York University Law Review, 86, 1814.
[15]
Tsai, C.H. (2015) The Application of a Personal Identification Database and Risk Management Mechanism. International Journal of Social Sciences and Education Research, 1, 1009-1016. https://doi.org/10.24289/ijsser.279112
[16]
Regan, P.M. (2002) Privacy as a Common Good in the Digital World. Information, Communication & Society, 5, 382-405. https://doi.org/10.1080/13691180210159328
[17]
Buccafurri, F., et al. (2018) Integrating Digital Identity and Blockchain. On the Move to Meaningful Internet Systems. OTM 2018 Conferences. Confederated International Conferences: CoopIS, C&TC, and ODBASE 2018, Valletta, 22-26 October 2018, 568-585.
[18]
Lim, S.Y., et al. (2018) Blockchain Technology the Identity Management and Authentication Service Disruptor: A Survey. International Journal on Advanced Science, Engineering and Information Technology, 8, 1735-1745. https://doi.org/10.18517/ijaseit.8.4-2.6838
[19]
Stratopoulos, T.C., Wang, V.X. and Ye, J. (2020) Blockchain Technology Adoption. Use of Corporate Disclosures to Identify the Stage of Blockchain Adoption. Accounting Horizons, 36, 197-220. https://doi.org/10.2308/HORIZONS-19-101
[20]
Ning, X., Ramirez, R. and Khuntia, J. (2021) Blockchain-Enabled Government Efficiency and Impartiality: Using Blockchain for Targeted Poverty Alleviation in a City in China. Information Technology for Development, 27, 599-616. https://doi.org/10.1080/02681102.2021.1925619
[21]
Clavin, J., et al. (2020) Blockchains for Government: Use Cases and Challenges. Digital Government: Research and Practice, 1, Article 22. https://doi.org/10.1145/3427097
[22]
Zarrin, J., et al. (2021) Blockchain for Decentralization of Internet: Prospects, Trends, and Challenges. Cluster Computing, 24, 2841-2866. https://doi.org/10.1007/s10586-021-03301-8
[23]
Mills, R.E., et al. (2011) Mapping Copy Number Variation by Population-Scale Genome Sequencing. Nature, 470, 59-65. https://doi.org/10.1038/nature09708
[24]
Eichler, E.E. (2019) Genetic Variation, Comparative Genomics, and the Diagnosis of Disease. New England Journal of Medicine, 381, 64-74. https://doi.org/10.1056/NEJMra1809315
[25]
Chaisson, M.J., Wilson, R.K. and Eichler, E.E. (2015) Genetic Variation and the de Novo Assembly of Human Genomes. Nature Reviews Genetics, 16, 627-640. https://doi.org/10.1038/nrg3933
[26]
Knight, J.C. (2010) Understanding Human Genetic Variation in the Era of High-Throughput Sequencing. EMBO Reports, 11, 650-652. https://doi.org/10.1038/embor.2010.126
[27]
Ellegren, H. and Galtier, N. (2016) Determinants of Genetic Diversity. Nature Reviews Genetics, 17, 422-433. https://doi.org/10.1038/nrg.2016.58
[28]
Collins, F.S., et al. (1998) New Goals for the US Human Genome Project: 1998-2003. Science, 282, 682-689. https://doi.org/10.1126/science.282.5389.682
[29]
Ikegawa, S. (2012) A Short History of the Genome-Wide Association Study: Where We Were and Where We Are Going. Genomics & Informatics, 10, 220-225. https://doi.org/10.5808/GI.2012.10.4.220
[30]
Gudbjartsson, D.F., et al. (2015) Large-Scale Whole-Genome Sequencing of the Icelandic Population. Nature Genetics, 47, 435-444. https://doi.org/10.1038/ng.3247
[31]
Senthilvel, S., et al. (2019) Development and Validation of an SNP Genotyping Array and Construction of a High-Density Linkage Map in Castor. Scientific Reports, 9, Article No. 3003. https://doi.org/10.1038/s41598-019-39967-9
[32]
Williams, L.M., et al. (2010) SNP Identification, Verification, and Utility for Population Genetics in a Non-Model Genus. BMC Genetics, 11, Article No. 32. https://doi.org/10.1186/1471-2156-11-32
[33]
The International HapMap Consortium (2005) A Haplotype Map of the Human Genome. Nature, 437, 1299-1320. https://doi.org/10.1038/nature04226
[34]
Miller, M.P. and Kumar, S. (2001) Understanding Human Disease Mutations through the Use of Interspecific Genetic Variation. Human Molecular Genetics, 10, 2319-2328. https://doi.org/10.1093/hmg/10.21.2319
[35]
Hinds, D.A., et al. (2006) Common Deletions and SNPs Are in Linkage Disequilibrium in the Human Genome. Nature Genetics, 38, 82-85. https://doi.org/10.1038/ng1695
[36]
Kruglyak, L. (1997) The Use of a Genetic Map of Biallelic Markers in Linkage Studies. Nature Genetics, 17, 21-24. https://doi.org/10.1038/ng0997-21
[37]
Xiong, M. and Jin, L. (1999) Comparison of the Power and Accuracy of Biallelic and Microsatellite Markers in Population-Based Gene-Mapping Methods. The American Journal of Human Genetics, 64, 629-640. https://doi.org/10.1086/302231
[38]
Tarach, P. (2021) Application of Polymerase Chain Reaction-Restriction Fragment length Polymorphism (RFLP-PCR) in the Analysis of Single Nucleotide Polymorphisms (SNPs). Acta Universitatis Lodziensis. Folia Biologica et Oecologica, 17, 48-53. https://doi.org/10.18778/1730-2366.16.14
[39]
Heaton, M.P., et al. (2002) Selection and Use of SNP Markers for Animal Identification and Paternity Analysis in US Beef Cattle. Mammalian Genome, 13, 272-281. https://doi.org/10.1007/s00335-001-2146-3
[40]
Handsaker, R.E., et al. (2015) Large Multiallelic Copy Number Variations in Humans. Nature Genetics, 47, 296-303. https://doi.org/10.1038/ng.3200
[41]
Nielsen, R., et al. (2011) Genotype and SNP Calling from Next-Generation Sequencing Data. Nature Reviews Genetics, 12, 443-451. https://doi.org/10.1038/nrg2986
[42]
Rehm, H.L., et al. (2013) ACMG Clinical Laboratory Standards for Next-Generation Sequencing. Genetics Medicine, 15, 733-747. https://doi.org/10.1038/gim.2013.92
[43]
Logsdon, G.A., Vollger, M.R. and Eichler, E.E. (2020) Long-Read Human Genome Sequencing and Its Applications. Nature Reviews Genetics, 21, 597-614. https://doi.org/10.1038/s41576-020-0236-x
[44]
Beck, J.J., et al. (2021) Biology and Genetics of Dizygotic and Monozygotic Twinning. In: Khalil, A., Lewi, L. and Lopriore, E., Eds., Twin and Higher-Order Pregnancies, Springer, New York, 31-50. https://doi.org/10.1007/978-3-030-47652-6_3
[45]
Ku, C.S., et al. (2010) The Discovery of Human Genetic Variations and Their Use as Disease Markers: Past, Present and Future. Journal of Human Genetics, 55, 403-415. https://doi.org/10.1038/jhg.2010.55
[46]
Miller, R.D., et al. (2005) High-Density Single-Nucleotide Polymorphism Maps of the Human Genome. Genomics, 86, 117-126. https://doi.org/10.1016/j.ygeno.2005.04.012
Jain, A.K., Prabhakar, S. and Pankanti, S. (2002) On the Similarity of Identical Twin Fingerprints. Pattern Recognition, 35, 2653-2663. https://doi.org/10.1016/S0031-3203(01)00218-7
[49]
Syvänen, A.C. (2001) Accessing Genetic Variation: Genotyping Single Nucleotide Polymorphisms. Nature Reviews Genetics, 2, 930-942. https://doi.org/10.1038/35103535
[50]
Shaw, G. (2013) Polymorphism and Single Nucleotide Polymorphisms (SNPs). BJU International, 112, 664-665. https://doi.org/10.1111/bju.12298
[51]
Taylor, J.G., et al. (2001) Using Genetic Variation to Study Human Disease. Trends in Molecular Medicine, 7, 507-512. https://doi.org/10.1016/S1471-4914(01)02183-9
[52]
Huang, T., Shu, Y. and Cai, Y.D. (2015) Genetic Differences among Ethnic Groups. BMC Genomics, 16, Article No. 1093. https://doi.org/10.1186/s12864-015-2328-0
[53]
Gibson, G. (2012) Rare and Common Variants: Twenty Arguments. Nature Reviews Genetics, 13, 135-145. https://doi.org/10.1038/nrg3118
[54]
Schork, N.J., et al. (2009) Common vs. Rare Allele Hypotheses for Complex Diseases. Current Opinion in Genetics & Development, 19, 212-219. https://doi.org/10.1016/j.gde.2009.04.010
[55]
Cawood, A. (1989) DNA Fingerprinting. Clinical Chemistry, 35, 1832-1837. https://doi.org/10.1093/clinchem/35.9.1832
[56]
Patzak, J., Vrba, L. and Matoušek, J. (2007) New STS Molecular Markers for Assessment of Genetic Diversity and DNA Fingerprinting in Hop (Humulus lupulus L.). Genome, 50, 15-25. https://doi.org/10.1139/g06-128
[57]
Lynch, M. (1988) Estimation of Relatedness by DNA Fingerprinting. Molecular Biology and Evolution, 5, 584-599.
[58]
Wilkinson, S., et al. (2011) Evaluation of Approaches for Identifying Population Informative Markers from High Density SNP Chips. BMC Genomic Data, 12, Article No. 45. https://doi.org/10.1186/1471-2156-12-45
[59]
Eberle, M.A., et al. (2007) Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels. PLOS Genetics, 3, e170. https://doi.org/10.1371/journal.pgen.0030170
[60]
Linck, E. and Battey, C. (2019) Minor Allele Frequency Thresholds Strongly Affect Population Structure Inference with Genomic Data Sets. Molecular Ecology Resources, 19, 639-647. https://doi.org/10.1111/1755-0998.12995
[61]
The International SNP Map Working Group (2001) A Map of Human Genome Sequence Variation Containing 1.42 Million Single Nucleotide Polymorphisms. Nature, 409, 928-933. https://doi.org/10.1038/35057149
[62]
Mardis, E.R. (2008) Next-Generation DNA Sequencing Methods. Annual Review of Genomics and Human Genetics, 9, 387-402. https://doi.org/10.1146/annurev.genom.9.081307.164359
[63]
Bleier, A., Goldfarb, A. and Tucker, C. (2020) Consumer Privacy and the Future of Data-Based Innovation and Marketing. International Journal of Research in Marketing, 37, 466-480. https://doi.org/10.1016/j.ijresmar.2020.03.006
[64]
Kuperberg, M. (2019) Blockchain-Based Identity Management: A Survey from the Enterprise and Ecosystem Perspective. IEEE Transactions on Engineering Management, 67, 1008-1027. https://doi.org/10.1109/TEM.2019.2926471
[65]
Kuo, T.T., et al. (2020) iDASH Secure Genome Analysis Competition 2018: Blockchain Genomic Data Access Logging, Homomorphic Encryption on GWAS, and DNA Segment Searching. BMC Medical Genomics, 13, Article No. 98. https://doi.org/10.1186/s12920-020-0715-0
[66]
Alshamrani, S.S. and Basha, A.F. (2021) IoT Data Security with DNA-Genetic Algorithm Using Blockchain Technology. International Journal of Computer Applications in Technology, 65, 150-159. https://doi.org/10.1504/IJCAT.2021.114988
[67]
Jin, X.L., et al. (2019) Application of a Blockchain Platform to Manage and Secure Personal Genomic Data: A Case Study of LifeCODE.ai in China. Journal of Medical Internet Research, 21, e13587. https://doi.org/10.2196/13587
[68]
Serada, A., Sihvonen, T. and Harviainen, J.T. (2021) CryptoKitties and the New Ludic Economy: How Blockchain Introduces Value, Ownership, and Scarcity in Digital Gaming. Games and Culture, 16, 457-480. https://doi.org/10.1177/1555412019898305
[69]
Ducuing, C. (2019) How to Make Sure My Cryptokitties Are Here Forever? The Complementary Roles of Blockchain and the Law to Bring Trust. European Journal of Risk Regulation, 10, 315-329. https://doi.org/10.1017/err.2019.39
[70]
Alghazwi, M., et al. (2022) Blockchain for Genomics: A Systematic Literature Review. Distributed Ledger Technologies: Research and Practice, 1, Article 11. https://doi.org/10.1145/3563044
[71]
Oldoni, F., Kidd, K.K. and Podini, D. (2019) Microhaplotypes in Forensic Genetics. Forensic Science International: Genetics, 38, 54-69. https://doi.org/10.1016/j.fsigen.2018.09.009
[72]
Pungila, C. and Negru. V. (2019) Accelerating DNA Biometrics In Criminal Investigations through GPU-Based Pattern Matching. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18, San Sebastián, 6-8 June 2018, Proceedings 13.
[73]
Bakken, S. (2021) Biometrics Light the Way for Secure Financial Services. Biometric Technology Today, 2021, 10-12. https://doi.org/10.1016/S0969-4765(21)00072-2
[74]
Mahier, J., et al. (2009) Biometric Authentication. In: Mehdi Khosrow-Pour, D.B.A. Ed., Encyclopedia of Information Science and Technology, IGI Global, Pennsylvania, 346-354. https://doi.org/10.4018/978-1-60566-026-4.ch059
[75]
Gürsoy, G., et al. (2022) Storing and Analyzing a Genome on a Blockchain. Genome Biology, 23, Article No. 134. https://doi.org/10.1186/s13059-022-02699-7
[76]
Oestreich, M., et al. (2021) Privacy Considerations for Sharing Genomics Data. EXCLI Journal, 20, Article 1243. https://doi.org/10.4135/9781071859544
[77]
Shabani, M. (2019) Blockchain-Based Platforms for Genomic Data Sharing: A De-Centralized Approach in Response to the Governance Problems? Journal of the American Medical Informatics Association, 26, 76-80. https://doi.org/10.1093/jamia/ocy149
[78]
Avellaneda, O., et al. (2019) Decentralized Identity: Where Did It Come from and Where Is It Going? IEEE Communications Standards Magazine, 3, 10-13. https://doi.org/10.1109/MCOMSTD.2019.9031542
[79]
Javed, I.T., et al. (2021) Health-ID: A Blockchain-Based Decentralized Identity Management for Remote Healthcare. Healthcare, 9, Article 712. https://doi.org/10.3390/healthcare9060712
[80]
Szalachowski, P. (2021) Password-Authenticated Decentralized Identities. IEEE Transactions on Information Forensics and Security, 16, 4801-4810. https://doi.org/10.1109/TIFS.2021.3116429