[1] Habermeier R., “Swappable Consensus.” issues/1304, 2018. Online; accessed 26 September 2021.

[2] Tang, W., “Re-Genesis.”, 2020. Online; accessed 26 September 2021.

[3] Research and Markets. , “Biometrics - Global Market Outlook (2018-2027).”, 2018. Online; accessed 26 September 2021.

[4] Emergen Research. , “Global Biometrics Market Size to Reach USD 99.63 Billion in 2027.”, 2021. Online; accessed 26 September 2021.

[5] Apple Support. , “About Face ID advanced technology.”, 2021. Online; accessed 26 September 2021.

[6] Global Industry Analysts, Inc, “Mobile Biometrics - Global Market Trajectory & Analytics.”, 2021. Online; accessed 26 September 2021.

[7] G. Davida, Y. Frankel, and B. Matt, “On enabling secure applications through off-line biometric identification,” in Proceedings. 1998 IEEE Symposium on Security and Privacy (Cat. No.98CB36186), pp. 148–157, 1998.

[8] N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometricsbased authentication systems,” IBM Systems Journal, vol. 40, no. 3, pp. 614–634, 2001.

[9] R. M. Bolle, J. H. Connell, and N. K. Ratha, “Biometric perils and patches,” Pattern Recognition, vol. 35, no. 12, pp. 2727–2738, 2002. Pattern Recognition in Information Systems.

[10] A. T. B. Jin, D. N. C. Ling, and A. Goh, “Biohashing: two factor authentication featuring fingerprint data and tokenised random number,” Pattern Recognition, vol. 37, no. 11, pp. 2245– 2255, 2004.

[11] A. Kong, K.-H. Cheung, D. Zhang, M. Kamel, and J. You, “An analysis of biohashing and its variants,” Pattern Recognition, vol. 39, no. 7, pp. 1359–1368, 2006.

[12] A. B. Teoh, Y. W. Kuan, and S. Lee, “Cancellable biometrics and annotations on biohash,” Pattern Recognition, vol. 41, no. 6, pp. 2034–2044, 2008.

[13] U. A. Rathgeb C., “A survey on biometric cryptosystems and cancelable biometrics,” EURASIP J. on Info. Security, no. 3, 2011.

[14] M. A. Syarif, T. S. Ong, A. B. J. Teoh, and C. Tee, “Improved biohashing method based on most intensive histogram block location,” in Neural Information Processing (C. K. Loo, K. S. Yap, K. W. Wong, A. T. Beng Jin, and K. Huang, eds.), (Cham), pp. 644–652, Springer International Publishing, 2014. 69

[15] B. J. Jisha Nair and S. Ranjitha Kumari, “A review on biometric cryptosystems,” A Review on Biometric Cryptosystems, vol. 6, no. 1, pp. 46–53, 2015.

[16] H. Kikuchi, K. Nagai, W. Ogata, and M. Nishigaki, “Privacy-preserving similarity evaluation and application to remote biometrics authentication,” in ., pp. 3–14, 10 2008.

[17] R. Belguechi, E. Cherrier, V. Alimi, P. Lacharme, and C. Rosenberger, An Overview on Privacy Preserving Biometrics. IntechOpen, 07 2011.

[18] , “Representation of image as a grid of pixels.” processing/images/sample_grid_a_square.png, 2021. Online; accessed 26 September 2021.

[19] Shyamal Patel and Johanna Pingel, “Introduction to Deep Learning: What Are Convolutional Neural Networks?.”, 2021. Online; accessed 26 September 2021.

[20] H. Gholamalinezhad and H. Khosravi, “Pooling methods in deep neural networks, a review,” 2020.

[21] C. Gentry, A. Sahai, and B. Waters, “Homomorphic encryption from learning with errors: Conceptually-simpler, asymptotically-faster, attribute-based,” in Advances in Cryptology – CRYPTO 2013 (R. Canetti and J. A. Garay, eds.), (Berlin, Heidelberg), pp. 75–92, Springer Berlin Heidelberg, 2013.

[22] T. Dinh, R. Steinfeld, and N. Bhattacharjee, “A lattice-based approach to privacy-preserving biometric authentication without relying on trusted third parties,” in Information Security Practice and Experience (J. K. Liu and P. Samarati, eds.), (Cham), pp. 297–319, Springer International Publishing, 2017.

[23] A. Abidin and A. Mitrokotsa, “Security aspects of privacy-preserving biometric authentication based on ideal lattices and ring-lwe,” in 2014 IEEE International Workshop on Information Forensics and Security (WIFS), pp. 60–65, 2014.

[24] Z. Brakerski and V. Vaikuntanathan, “Fully homomorphic encryption from ring-lwe and security for key dependent messages,” in Advances in Cryptology – CRYPTO 2011 (P. Rogaway, ed.), (Berlin, Heidelberg), pp. 505–524, Springer Berlin Heidelberg, 2011.

[25] J. Chotard, E. Dufour-Sans, R. Gay, D. H. Phan, and D. Pointcheval, “Decentralized multiclient functional encryption for inner product.” Cryptology ePrint Archive, Report 2017/989, 2017.

[26] D. Froelicher, P. Egger, J. S. Sousa, J. L. Raisaro, Z. Huang, C. Mouchet, B. Ford, and J.-P. Hubaux, “Unlynx: A decentralized system for privacy-conscious data sharing,” Proceedings on Privacy Enhancing Technologies, vol. 2017, pp. 232 – 250, 2017.

[27] G. Kaur and C. K. Verma, “Comparative analysis of biometric modalities,” in ., 2014.

[28] S. Jaiswal, S. S. Bhadauria, and D. S. Jadon, “Biometric: Case study,” Journal of Global Research in Computer Sciences, vol. 2, pp. 19–49, 2011.

[29] A. K. Jain, R. Bolle, and S. Pankanti, Biometrics: Personal Identification in Networked Society. Norwell, Massachusetts: Kluwer Academic Publishers, 1999.

[30] A. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 14, pp. 4 – 20, 02 2004. 70

[31] A. Weaver, “Biometric authentication,” Computer, vol. 39, pp. 96–100, feb 2000.

[32] V. P. Venkatesan and K. Senthamaraikannan, “A comprehensive survey on various biometric systems,” in ., 2018.

[33] B. Choudhury, P. Then, B. Issac, V. Raman, and M. Haldar, “A survey on biometrics and cancelable biometrics systems,” International Journal of Image and Graphics, vol. 18, p. 1850006, 01 2018.

[34] A. Raju and V. Udayashankara, “A survey on unimodal, multimodal biometrics and its fusion techniques,” International Journal of Engineering and Technology(UAE), vol. 7, pp. 689–695, 12 2018.

[35] F. Sadikoglu and S. Uzelaltınbulat, “Biometric retina identification based on neural network,” ¨ Procedia Computer Science, vol. 102, pp. 26–33, 12 2016.

[36] L. Rabiner and B.-H. Juang, Fundamentals of Speech Recognition. USA: Prentice-Hall, Inc., 1993.

[37] M. Hanmandlu and S. Vasikarla, “Online biometric authentication using facial thermograms,” in ., pp. 1–6, 10 2012.

[38] A. Abaza, A. Ross, C. Hebert, M. Harrison, and M. Nixon, “A survey on ear biometrics,” ACM Computing Surveys (CSUR), vol. 45, 02 2013.

[39] K. Bowyer, K. Hollingsworth, and P. Flynn, “Image understanding for iris biometrics: A survey,” Computer Vision and Image Understanding, vol. 110, pp. 281–307, 05 2008.

[40] M. Shu, Y. Liu, and H. Fang, “Identification authentication scheme using human body odour,” 2014 IEEE International Conference on Control Science and Systems Engineering, pp. 171– 174, 2014.

[41] S. D. Finn E., Shen X., “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat Neurosci, vol. 18, p. 1664–1671, 2015.

[42] F. E. H. L. and J. D.C., “Layer-dependent activity in human prefrontal cortex during working memory,” Nat Neurosci, vol. 22, p. 1687–1695, 2019.

[43] A. Demertzi, E. Tagliazucchi, S. Dehaene, G. Deco, P. Barttfeld, F. Raimondo, C. Martial, D. Fern´andez-Espejo, B. Rohaut, H. U. Voss, N. D. Schiff, A. M. Owen, S. Laureys, L. Naccache, and J. D. Sitt, “Human consciousness is supported by dynamic complex patterns of brain signal coordination,” Science Advances, vol. 5, no. 2, p. eaat7603, 2019.

[44] A. Kong, D. Zhang, and M. S. Kamel, “A survey of palmprint recognition,” Pattern Recognition, vol. 42, pp. 1408–1418, 07 2009.

[45] J. Daugman, “How iris recognition works,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, pp. 21–30, 2004.

[46] Chien Le and Raj Jain, “A Survey of Biometrics Security Systems.” https://www.cse.wustl. edu/~jain/cse571-11/ftp/biomet.pdf, 2011. Online; accessed 26 September 2021.

[47] S. Bhable, S. Kayte, R. Maher, J. Kayte, and C. Kayte, “Dna biometric,” IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), vol. 5, pp. 2319–4200, 11 2015.

[48] R. Garcia-Martin and R. Sanchez-Reillo, “Vein biometric recognition on a smartphone,” IEEE Access, vol. 8, pp. 104801–104813, 2020. 71

[49] S. Bargal, A. Welles, C. Chan, S. Howes, S. Sclaroff, E. Ragan, C. Johnson, and C. Gill, “Imagebased ear biometric smartphone app for patient identification in field settings,” VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; VISIGRAPP, Proceedings, vol. 3, pp. 171–179, 01 2015.

[50] A. F. Abate, M. Nappi, and S. Ricciardi, “Smartphone enabled person authentication based on ear biometrics and arm gesture,” in 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 003719–003724, 2016.

[51] E. Rahmawati, M. Listyasari, A. Aziz, S. Sukaridhoto, F. A. Damastuti, M. M. Bachtiar, and A. Sudarsono, “Digital signature on file using biometric fingerprint with fingerprint sensor on smartphone,” in ., pp. 234–238, 09 2017.

[52] G. Goudelis, A. Tefas, and I. Pitas, “Emerging biometric modalities: A survey,” Journal on Multimodal User Interfaces, vol. 2, pp. 217–235, 12 2009.

[53] Samsung, “Security.”, 2021. Online; accessed 26 September 2021.

[54] A. Jain, K. Nandakumar, and A. Nagar, “Biometric template security,” EURASIP Journal on Advances in Signal Processing, vol. 2008, 03 2008.

[55] K. A. Professor, “A review of various attacks on biometrics system and their known solutions,” in ., 2011.

[56] R. M. Bolle, J. H. Connell, and N. K. Ratha, “Biometric perils and patches,” Pattern Recognition, vol. 35, no. 12, pp. 2727–2738, 2002. Pattern Recognition in Information Systems.

[57] G. Mai, K. Cao, P. C. Yuen, and A. K. Jain, “Face image reconstruction from deep templates,” CoRR, vol. abs/1703.00832, 2017.

[58] Braingate, “braingate, turning thought into action.”, 2021. Online; accessed 26 September 2021.

[59] Neuralink, “Breakthrough Technology for the Brain.”, 2021. Online; accessed 26 September 2021.

[60] Brainlab, “Brainlab.”, 2021. Online; accessed 26 September 2021.

[61] Facebook, “F8 2017: AI, Building 8 and More Technology Updates From Day Two.” https://, 2017. Online; accessed 26 September 2021.

[62] M. D. . C. E. Makin J.G., “Machine translation of cortical activity to text with an encoder–decoder framework,” Nat Neurosci, vol. 23, p. 575–582, 2020.

[63] S. Mudgal, S. Sharma, J. Chaturvedi, and A. Sharma, “Brain computer interface advancement in neurosciences: Applications and issues,” Interdisciplinary Neurosurgery, vol. 20, p. 100694, 02 2020.

[64] G. Pfurtscheller, B. Allison, C. Brunner, G. Bauernfeind, T. Solis-Escalante, R. Scherer, T. Zander, G. M¨uller-Putz, C. Neuper, and N. Birbaumer, “The hybrid bci,” Frontiers in neuroscience, vol. 4, p. 30, 04 2010.

[65] G. M¨uller-Putz, R. Leeb, J. d. R. Millan, P. Horki, A. Kreilinger, G. Bauernfeind, B. Allison, C. Brunner, and R. Scherer, Principles of Hybrid Brain–Computer Interfaces, pp. 355–373. ., 01 2013. 72

[66] I. Choi, I. Rhiu, Y. Lee, M. H. Yun, and C. S. Nam, “A systematic review of hybrid braincomputer interfaces: Taxonomy and usability perspectives,” PLOS ONE, vol. 12, pp. 1–35, 04 2017.

[67] D. Yang, H. Nguyen, and W.-Y. Chung, “A synchronized hybrid brain-computer interface system for simultaneous detection and classification of fusion eeg signals,” Complexity, vol. 2020, pp. 1–11, 06 2020.

[68] K.-S. Hong and M. Khan, “Hybrid brain–computer interface techniques for improved classification accuracy and increased number of commands: A review,” Frontiers in Neurorobotics, vol. 11, 07 2017.

[69] S. Sahar and A. Maleki., “Recent advances in hybrid brain-computer interface systems: A technological and quantitative review.,” Basic and clinical neuroscience, vol. 9, pp. 373–388, 2018.

[70] T. Blum, R. Stauder, E. Euler, and N. Navab, “Superman-like x-ray vision: Towards braincomputer interfaces for medical augmented reality,” in 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 271–272, 2012.

[71] X.-S. Hu, T. D. Nascimento, M. C. Bender, T. Hall, S. Petty, S. O’Malley, R. P. Ellwood, N. Kaciroti, E. Maslowski, and A. F. DaSilva, “Feasibility of a real-time clinical augmented reality and artificial intelligence framework for pain detection and localization from the brain,” Journal of medical Internet research, vol. 21, p. e13594, June 2019.

[72] S. Park, H. Cha, J. Kwon, H. Kim, and C. Im, “Development of an online home appliance control system using augmented reality and an ssvep-based brain-computer interface,” in 8th International Winter Conference on Brain-Computer Interface, BCI 2020, 8th International Winter Conference on Brain-Computer Interface, BCI 2020, Institute of Electrical and Electronics Engineers Inc., Feb. 2020. Publisher Copyright: © 2020 IEEE.; null ; Conference date: 26-02-2020 Through 28-02-2020.

[73] D. Friedman, ““brain art: Brain-computer interfaces for artistic expression”,” Brain-Computer Interfaces, vol. 7, no. 1-2, pp. 36–37, 2020.

[74] A. Benitez-Andonegui, R. Burden, R. Benning, R. M¨ockel, M. L¨uhrs, and B. Sorger, “An augmented-reality fnirs-based brain-computer interface: A proof-of-concept study,” Front Neurosci, vol. 14, 2020.

[75] G. Liberati, A. Pizzimenti, L. Simione, A. Riccio, F. Schettini, M. Inghilleri, D. Mattia, and F. Cincotti, “Developing brain-computer interfaces from a user-centered perspective: Assessing the needs of persons with amyotrophic lateral sclerosis, caregivers, and professionals.,” Applied ergonomics, vol. 50, p. 139–146, 2015.

[76] K. A, H. EM, and R. A, “The user-centered design as novel perspective for evaluating the usability of bci-controlled applications.,” PLoS One., vol. 9, 2014.

[77] F. Nijboer, “Technology transfer of brain-computer interfaces as assistive technology: Barriers and opportunities,” Annals of Physical and Rehabilitation Medicine, vol. 58, no. 1, pp. 35– 38, 2015. Brain Computer Interfaces (BCIs) / Coordinated by Jacques Luaut´e and Isabelle Laffont.

[78] D. Baars, “Towards self-sovereign identity using blockchain technology,” October 2016.

[79] Ori Jacobovitz, “Blockchain for Identity Management.” ~frankel/TechnicalReports/2016/16-02.pdf, 2016. Online; accessed 26 September 2021. 73

[80] Andrew Tobin and Drummond Reed, “The Inevitable Rise of Self-Sovereign Identity.”, 2016. Online; accessed 26 September 2021.

[81] P. Dunphy and F. A. Petitcolas, “A first look at identity management schemes on the blockchain,” IEEE Security Privacy, vol. 16, no. 4, pp. 20–29, 2018.

[82] J. S. Hammudoglu, J. Sparreboom, J. I. Rauhamaa, J. K. Faber, L. C. Guerchi, I. P. Samiotis, S. P. Rao, and J. A. Pouwelse, “Portable trust: biometric-based authentication and blockchain storage for self-sovereign identity systems,” 2017.

[83] P. Garcia, “Biometrics on the blockchain,” Biometric Technology Today, vol. 2018, no. 5, pp. 5–7, 2018.

[84] A. Othman and J. Callahan, “The horcrux protocol: A method for decentralized biometricbased self-sovereign identity,” in 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1–7, 2018.

[85] Maciek Laskus, “Decentralized Identity Trilemma.”, 2018. Online; accessed 26 September 2021.

[86] J. R. Douceur, “The Sybil Attack.”, 2002. Online; accessed 26 September 2021.

[87] R. John, J. P. Cherian, and J. J. Kizhakkethottam, “A survey of techniques to prevent sybil attacks,” in 2015 International Conference on Soft-Computing and Networks Security (ICSNS), pp. 1–6, 2015.

[88] A. M. Bhise and S. D. Kamble, “Review on detection and mitigation of sybil attack in the network,” Procedia Computer Science, vol. 78, pp. 395–401, 2016. 1st International Conference on Information Security & Privacy 2015.

[89] D. Siddarth, S. Ivliev, S. Siri, and P. Berman, “Who watches the watchmen? A review of subjective approaches for sybil-resistance in proof of personhood protocols,” CoRR, vol. abs/2008.05300, 2020.

[90] Christopher Allen, “The Path to Self-Sovereign Identity.” http://www.lifewithalacrity. com/2016/04/the-path-to-self-soverereign-identity.html, 2016. Online; accessed 26 September 2021.

[91] V. Buterin, “Problems.” 89fd07ffff8b042134e4ca67a0ce143d574016bd, 2014. Online; accessed 26 September 2021.

[92] V. Buterin, “Hard Problems in Cryptocurrency: Five Years Later.” general/2019/11/22/progress.html, 2019. Online; accessed 26 September 2021.

[93] M. Al-Qurishi, M. Al-Rakhami, A. Alamri, M. Alrubaian, S. M. M. Rahman, and M. S. Hossain, “Sybil defense techniques in online social networks: A survey,” IEEE Access, vol. 5, pp. 1200–1219, 2017.

[94] A. Alharbi, M. Zohdy, D. Debnath, R. Olawoyin, and G. P. Corser, “Sybil attacks and defenses in internet of things and mobile social networks,” in ., 2019.

[95] P. Gu, R. Khatoun, Y. Begriche, and A. Serhrouchni, “Support vector machine (svm) based sybil attack detection in vehicular networks,” in 2017 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6, 2017. 74

[96] K. Zhang, X. Liang, R. Lu, K. Yang, and X. S. Shen, “Exploiting mobile social behaviors for sybil detection,” in 2015 IEEE Conference on Computer Communications (INFOCOM), pp. 271–279, 2015.

[97] Y. Muliadi, M. Baker, D. Rosenthal, P. Maniatis, M. Roussopoulos, and T. Giuli, “Preserving peer replicas by rate-limited sampled voting in lockss,” ., 03 2003.

[98] B. Awerbuch and C. Scheideler, “Group spreading: A protocol for provably secure distributed name service,” in ICALP, 2004.

[99] P. Maniatis, D. S. H. Rosenthal, M. Roussopoulos, and M. Baker, “Lockss: A peer-to-peer digital preservation system,” ACM Transactions on Computer Systems, vol. 23, p. 2005, 2003.

[100] B. Levine, C. Shields, and N. Margolin, “A survey of solutions to the sybil attack,” Technical Report of Univ of Massachussets Amherst, vol. 2006–052, 11 2005.

[101] N. Margolin and B. Levine, “Informant: Detecting sybils using incentives,” in ., vol. 4886, pp. 192–207, 02 2007.

[102] M. B. Shareh, H. Navidi, H. H. S. Javadi, and M. HosseinZadeh, “Preventing sybil attacks in p2p file sharing networks based on the evolutionary game model,” Information Sciences, vol. 470, pp. 94–108, 2019.

[103] M. B. Shareh, H. Navidi, H. H. S. Javadi, and M. Hosseinzadeh, “A new incentive mechanism to detect and restrict sybil nodes in p2p file-sharing networks with a heterogeneous bandwidth,” Journal of AI and Data Mining, 2020.

[104] F. Wang and P. De Filippi, “Self-sovereign identity in a globalized world: Credentials-based identity systems as a driver for economic inclusion,” Frontiers in Blockchain, vol. 2, p. 28, 2020.

[105] B. Ford and R. B¨ohme, “Rationality is self-defeating in permissionless systems,” 2019.

[106] S. A. Williams, V. Diordiiev, and L. Berman, “Arweave: A protocol for economically sustainable information permanence,” in ., 2019.

[107] Daniel Larimer, “The Hidden Costs of Bitcoin.”, 2013. Online; accessed 26 September 2021.

[108] Bitshares, “Bitshares.”, 2021. Online; accessed 26 September 2021.

[109] V. Buterin, “DAOs, DACs, DAs and More: An Incomplete Terminology Guide.”, 2014. Online; accessed 26 September 2021.

[110] V. Buterin, “Ethereum Whitepaper.”, 2013. Online; accessed 26 September 2021.

[111] J. Hyland, Democratic Theory: The Philosophical Foundations. Manchester: Manchester University Press, 1995.

Last updated