Web 3.0 and its Potential Impact on Privacy Shifting Left in the Development Process

Authors

  • Kiran Sharma Panchangam Nivarthi 31108 Algonquin Trail, Chisago City, MN, 55013, USA
  • Sudha Balajinaidu 15251 Pleasant Valley Rd, Center City, MN 55012

Keywords:

Web 3.0, Shift-left privacy

Abstract

The concept of Web 3.0 as the semantic web has been around since the early 2000s, and its decentralized interpretation gained more traction when the term was coined by Ethereum’s co-founder Gavin Wood. New programming languages were identified as the first enablers of Web 3.0, but under its new interpretation, other enabling technologies were identified. The three most significant of which are Artificial Intelligence (AI), Machine Learning (ML), and blockchain. IoT is both a concurrent technology and an enabler. Security and privacy-related challenges with the enabler technologies are already being identified and addressed. The privacy challenges associated with Web 3.0 as a whole are more difficult to identify due to multiple reasons, including the nascent form of the technology, the non-standardized definition of Web 3.0, and privacy (And compliance) concerns associated with decentralization. A decentralized version of the internet has the potential to evoke new, unprecedented privacy challenges, some of which may be addressed with further advances in blockchain (a key enabler). Other challenges and trends are associated with the other Web 3.0 enabler, i.e., artificial intelligence. Despite a wide variety of privacy challenges, there is a strong probability that Web 3.0 is highly likely to push privacy left in the development process. Many of the identified challenges with underlying Web 3.0 technologies can be better addressed at the early stages of the development process. Even though we have yet to see how development culture, our approach to privacy, and Web 3.0 as a tech will evolve, especially considering the myriad of new ethical concerns associated with AI, these factors may not impede privacy's shift to the left in Web 3.0.

References

M. Lacity and S. Lupien, "Restoring Trust with Blockchains," in Blockchain Fundamentals for Web 3.0, Epic Books, 2022.

O. Lassila and J. Hendler, "Embracing “Web 3.0”," IEEE Internet Computing, vol. 11, no. 3, pp. 90-93, 2007.

J. Hendler, "Web 3.0 Emerging," IEEE Computers, vol. 42, no. 1, pp. 111-113, 2009.

T. C. Hengjin Cai, "AnArchitecture for Web 3.0 and the Emergence of Spontaneous Time Order," 2022. [Online]. Available: https://doi.org/10.48550/arXiv.2202.10619.

Y. Lin, Z. Gao, H. Du, D. Niyato, J. Kang, R. Deng, and X. S. Shen, "A Unified Blockchain-Semantic Framework for Wireless Edge Intelligence Enabled Web 3.0," 2022. [Online]. Available: https://doi.org/10.48550/arXiv.2210.15130.

R. Rudman and R. Bruwer, "Defining Web 3.0: opportunities and challenges," The Electronic Library, vol. 34, no. 1, 2016.

C. Chen, L. Zhang, Y. Li, T. Liao, S. Zhao, Z. Zheng, H. Huang and J. Wu, "When Digital Economy Meets Web3.0: Applications and Challenges," IEEE Open Journal of the Computer Society, vol. 3, pp. 233-245, 2022.

S. Mishra and M. A. Srivastava, "WEB 3.0 TECHNOLOGY," International Journal of Research Publication and Reviews, vol. 3, no. 3, pp. 1755-1759, 2022.

A. K. Goel, R. Bakshi, and K. K. Agrawal, "Web 3.0 and Decentralized Applications," in MDPI - 2nd International Conference on Innovative Research in Renewable Energy Technologies (IRRET 2022), West Bengal, India, 2022.

M. R. Bruwer and M. Rudman, "Web 3.0: Governance, Risks and Safeguards," Journal of Applied Business Research, vol. 31, no. 3, pp. 1037-1056, 2015.

P. Winter, A. H. Lorimer, P. Snyder and B. Livshits, "What's in Your Wallet? Privacy and Security Issues in Web 3.0," 2021. [Online]. Available: https://doi.org/10.48550/arXiv.2109.06836.

A. N. Turi, "Currency Under the Web 3.0 Economy," Technologies for Modern Digital Entrepreneurship, pp. 155-186, 2020.

V. Findlay, "Security and Privacy Issues of Web 3.0," Cyber Security and Asset/Information Securitization, 2015.

F. A. Alabdulwahhab, "Web 3.0: The Decentralized Web," in 2018 1st International Conference on Computer Applications & Information Security (ICCAIS), Riyadh, Saudi Arabia, 2018.

S. Singh, P. K. Sharma, B. Yoon, M. Shojafar, G. H. Cho and I.-H. Ra, "Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city," Sustainable Cities and Society, vol. 63, 2020.

Y. Sun, J. Liu, J. Wang, Y. Cao, and N. Kato, "When Machine Learning Meets Privacy in 6G: A Survey," IEEE Communications Surveys & Tutorials, vol. 22, no. 4, 2020.

A. Rhayem, M. B. A. Mhiri, and F. Gargouri, "Semantic Web Technologies for the Internet of Things: Systematic Literature Review," Internet Of Things, vol. 11, 2020.

L. Tawalbeh, F. Muheidat, M. Tawalbeh, and M. Quwaider, "IoT Privacy and Security: Challenges and Solutions," Applied Sciences, vol. 10, 2020.

U. Gasser and V. A. Almeida, "A Layered Model for AI Governance," IEEE Internet Computing, vol. 21, no. 6, pp. 58-62, 2017.

"Gartner Identifies Top Five Trends in Privacy Through 2024," 2022. [Online]. Available: https://www.gartner.com/en/newsroom/press-releases/2022-05-31-gartner-identifies-top-five-trends-in-privacy-through-2024.

D. Roselli, J. Matthews, and N. Talagala, "Managing Bias in AI," in WWW '19: Companion Proceedings of The 2019 World Wide Web Conference, San Francisco; US, 2019.

E. D. Cristofaro, "AnOverview of Privacy in Machine Learning," arXiv: Machine Learning, 2020.

N. Papernot, P. McDaniel, A. Sinha, and M. Wellman, "SoK: Towards the Science of Security and Privacy in Machine Learning," arXiv: Cryptography and Security.

S. Qahtan, K. Yatim, H. Zulzalil, M. H. Osman, A. A. Zaidan, and H. A. Alsattard, "Review of healthcare industry 4.0 application-based blockchain in terms of security and privacy development attributes: Comprehensive taxonomy, open issues and challenges and recommended solution," Journal of Network and Computer Applications, vol. 209, 2023.

D. Wang, J. Zhao and Y. Wang, "A Survey on Privacy Protection of Blockchain: The Technology and Application," IEEE Access, vol. 8, pp. 108766-108781, 2020.

M. Jones, M. Johnson, M. Shervey, J. T. Dudley and N. Zimmerman, "Privacy-Preserving Methods for Feature Engineering Using Blockchain: Review, Evaluation, and Proof of Concept," Journal of Medical Internet Research, vol. 21, no. 8, 2019.

S. M. Hizam, W. Ahmed, H. Akter, I. Sentosa and M. N. Masrek, "Web 3.0 Adoption Behavior: PLS-SEM and Sentiment Analysis," arXiv, 2022.

G. Hatzivasilis, I. Askoxylakis, G. Alexandris, D. Anicic, A. Bröring, V. Kulkarni, K. Fysarakis and G. Spanoudakis, "The Interoperability of Things: Interoperable solutions as an enabler for IoT and Web 3.0," in 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Barcelona, Spain, 2018.

X. Liu, L. Xie, Y. Wang, J. Zou, J. Xiong, Z. Ying, and A. V. Vasilakos, "Privacy and Security Issues in Deep Learning: A Survey," IEEE Access, vol. 9, pp. 4566 - 4593, 2020.

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Published

2023-02-03

How to Cite

Panchangam Nivarthi, K. S., & Balajinaidu, S. (2023). Web 3.0 and its Potential Impact on Privacy Shifting Left in the Development Process. American Scientific Research Journal for Engineering, Technology, and Sciences, 91(1), 78–86. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/8560

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