Artificial Intelligence and GDPR: New Levers for Investment in Blockchain

Introduction

The rise of blockchain has opened up new investment avenues, while raising crucial questions about data security and regulatory compliance. With the General Data Protection Regulation (GDPR) being more and more applied in Europe, investors are placing increased importance on companies' compliance practices. This article looks at the revolutionary role of artificial intelligence (AI) in strengthening GDPR compliance and explores how this is transforming the criteria for investing in blockchain-related products.

The International Landscape of Data Protection Regulations

While the GDPR (General Data Protection Regulation) is often considered the gold standard for data protection in Europe, it is important to recognize that it is one of many regulatory frameworks across the world which govern the collection, processing and sharing of personal information. Each legislative framework reflects an approach that takes into account the cultural, social and political specificities of its jurisdiction.

In America, for example, California has taken proactive steps with the CCPA (California Consumer Privacy Act), giving consumers extensive rights over their personal data. In Brazil, the LGPD (Lei Geral de Prote??o de Dados) establishes a framework similar to the GDPR for Brazilian residents, highlighting the growing importance of data protection in the southern hemisphere.

In Asia, Thailand adopted the PDPA (Personal Data Protection Act), which imposes strict requirements on companies to manage personal data, while the United Kingdom, after leaving the EU, adopted the UK-GDPR , adapting the European GDPR in the context of its own legal system.

Canada is not left out with PIPEDA (Personal Information Protection and Electronic Documents Act), which applies to the private sector and imposes obligations regarding consent, access and transparency.

In Europe itself, in addition to the GDPR, the ePrivacy framework specifies rules on the confidentiality of electronic communications, and the IAB TCF (Interactive Advertising Bureau's Transparency & Consent Framework) provides a guide for regulatory-compliant digital advertising.

In France, the CNIL (National Commission for Information Technology and Liberties) ensures the application of these standards, acting as a guardian of personal data.

This regulatory diversity presents a significant challenge for businesses operating globally. It is crucial to develop a compliance strategy that not only respects local laws, but also accommodates fundamental data protection principles that transcend national borders.

Latest Developments on Blockchains and GDPR

Arthur Cox (2023) discusses how blockchain technology could offer innovative technical solutions for many GDPR compliance issues, while raising the important question of whether these solutions can be integrated under the GDPR framework.

Simmons & Simmons (2023) report that the Financial Conduct Authority (FCA) has announced a new set of rules for cryptocurrency marketing, which could have a significant impact on GDPR compliance in the blockchain space .

Advisera (2023) explores how GDPR authorities view blockchain technology, highlighting the need to harmonize this technology with privacy regulations and the main steps towards this compliance.

GDPR Compliance as an Investment Criterion

The impact of GDPR fines on businesses in 2023 has been significant, marking a record year for financial penalties. This development highlights the growing importance of GDPR compliance in the blockchain sector, particularly for investors evaluating opportunities in the technology. The fines imposed on companies like Meta and Amazon highlight the financial and reputational consequences of non-compliance, aspects crucial to investment decisions.

In 2023, record fines were imposed on major technology companies for various GDPR violations. For example, Meta was fined a historic €1.2 billion by the Irish Data Protection Commission for transferring personal data of its European users to the United States without adequate data protection mechanisms. This record fine serves as a clear warning to other businesses that GDPR requirements must be taken seriously and that non-compliance can result in severe financial consequences.

In addition to Meta, Amazon was also fined €746 million by Luxembourg's National Data Protection Commission due to violations related to its ad targeting system carried out without proper consent. These examples clearly illustrate how GDPR fines can significantly influence investment decisions, emphasizing GDPR compliance as a critical criterion for evaluating blockchain companies.

Another notable case is that of Criteo, a French advertising technology company, which was fined €40 million for failing to obtain user consent regarding targeted advertising. This case serves as a reminder to businesses around the world of the importance of GDPR compliance, particularly when it comes to obtaining informed consent from users.

These examples show that investors should pay particular attention to how blockchain companies manage GDPR compliance. A company that demonstrates strong GDPR compliance is likely to be more attractive to investors, as this reduces the financial and reputational risk associated with non-compliance. Additionally, it indicates that the company has technological maturity and an ability to navigate a complex regulatory environment, important factors for blockchain investors.

In conclusion, the 2023 GDPR fines, reaching over €1.6 billion, highlight the critical importance of compliance in today's data-driven landscape. To avoid incurring costly penalties, organizations should prioritize obtaining informed consent from users, ensuring secure data transfers outside the EU, and adhering to regulations regarding children's data protection.

Enforcement of data protection regulations shows no signs of slowing down – so organizations must learn from the mistakes of others and take proactive steps to protect user privacy and reduce risks, build trust and avoid consequences legal and reputational risks associated with non-compliance with the GDPR AI and Data Governance Integrating artificial intelligence (AI) into data governance is crucial to ensuring GDPR compliance, and several real-world examples and practical guidelines illustrate how this can be achieved.

AI Development in Compliance with GDPR

The CNIL has published practical guidelines for creating learning bases for AI systems, focusing on the development phase of AI tools (AI design and training), excluding the phase implementation (calibration, use, maintenance). These recommendations address issues such as determining the purposes of processing and limited retention periods, which are often seen as a barrier to some AI applications.

Ethical Integration of AI into Data Governance

Organizations must address aspects such as transparency, data minimization, and privacy protection when integrating AI. AI systems must be designed to be explainable and fair, avoiding “black boxes” and ensuring that algorithms are understandable and fair. Privacy Impact Assessments (DPIAs) are essential for identifying and addressing potential privacy risks.

Consent Management and the Right to be Forgotten

AI can be used to improve consent management by automating data classification and helping identify and categorize sensitive data types. Additionally, AI systems can be configured to effectively respond to user requests under the right to be forgotten, ensuring that user rights are respected in accordance with GDPR.

In summary, integrating AI into data governance offers many opportunities to improve GDPR compliance, but it requires a careful and strategic approach. Organizations must not only integrate AI into their data governance systems, but also ensure that these systems are in line with ever-changing regulations.

Data Security and Investment Decision

The impact of artificial intelligence (AI) on data security is a crucial factor in investment decisions, especially in the context of blockchain. Advances in AI enable early detection of data breaches and in-depth analysis of security risks, providing additional assurance to investors.

Recent studies show that extensive use of AI in automated processes can significantly reduce costs associated with data breaches. For example, an IBM study found that widespread adoption of AI saved nearly $1.8 million in data breach costs and accelerated the identification and containment of breaches. violations lasting more than 100 days on average. These results highlight the importance of AI in securing data and proactive risk management.

In one real-world case, Seyfarth's cybersecurity lawyers began using AI in their processes, including assessing their Fortune 200 clients' personally identifiable data (PI) breach incidents. They used the solution AI-powered Text IQ for Privacy in a Proof of Concept project to identify PI after a customer data breach. The results of this comparative study between human and machine evaluation showed significant efficiency and accuracy offered by AI.

These examples clearly demonstrate how integrating AI into data governance can improve GDPR compliance and positively influence investment decisions. AI's ability to quickly identify potential threats and security vulnerabilities is a major asset for companies looking to attract investment in the blockchain space.

Expert Opinions on GDPR Compliance in Blockchain Applications

According to an article from FinTech Global (2023), there is an ongoing debate about the harmonious coexistence between blockchain and GDPR, particularly regarding the classification of hashed data as personal information under GDPR.

A systematic review of the literature presented by ScienceDirect (2023) reveals three main issues linked to the tension between the GDPR and public blockchain systems: the difficulties of exercising data rights, the challenges of anonymization and the governance of data.

A document from CEUR-WS (2023) highlights that GDPR compliance represents a significant challenge for blockchain, requiring a change in approach to move towards better harmonization.

Example of GDPR Request in a Blockchain Context

“ Dear Data Protection Officer,

As a user of your company's services based on blockchain technology, I am contacting you to exercise my rights under Article 15 of the GDPR. I ask you to provide me with details of the specific categories of personal data you process about me, as well as the source of that data.

I am also interested in the following information:

1. What are the purposes and legal basis for processing my data?

2. What security measures have you put in place to protect my data?

3. With which third parties do you share my data, and for what purpose?

4. How long will my personal data be kept?

5. How can I exercise my right to rectify or delete my data, particularly in a blockchain system known for its immutability?

6. If a data breach occurs, how am I informed and what steps do you take to mitigate the risks?

Your response will not only serve to clarify my understanding of the management of my personal data, but also to assess your company's compliance with the GDPR. I look forward to your detailed response.

Sincerely,

A user concerned about the confidentiality of his data. ?

Analysis and Solutions for Each Issue Raised in the Letter: A Guide for Investors

Purposes and Legal Basis of Processing

Importance for Investors : Evaluate how the company explains the purpose and legal basis of data processing. Transparency and compliance in this area reflect strong data governance.

Role of AI in Compliance : Examine the use of AI for compliance analysis and consent management. Companies that deploy advanced AI solutions for these tasks demonstrate a commitment to innovation and regulatory compliance.

Security Measures and Data Sharing

Investment Criterion : How a company manages data security and sharing with third parties is a key indicator of its technological maturity. Look for strong encryption and authentication policies.

AI Integration and Alternative Solutions : Adopting reCAPTCHA and blockchain-friendly Captcha solutions for bot protection can indicate a proactive approach to data security.

Right of Rectification and Erasure

Challenge for Immutable Blockchains : Solutions like chameleon hashing and linked multidigital signature show how a blockchain company can manage the rectification and erasure of data while respecting immutability.

Outlook for Investors : Companies integrating these innovative technologies offer attractive investment potential, as they demonstrate an ability to solve complex compliance issues.

Data Breach Management

Evaluating AI Strategies : A company's ability to use AI for detection and rapid response to security incidents is a key indicator of its cybersecurity competency.

Implication for Investors : A proactive and technologically advanced approach in this area is a positive sign for investors, indicating effective risk management.

Blockchain used

Comparison with Bitcoin : Less flexible, mainly for financial transactions.

Comparison with Cardano : More focused on research and sustainability, potential for GDPR compliance.

Ethereum Specifics and GDPR: A Practical Guide to Compliance

Integrating Ethereum into business operations poses unique challenges in terms of General Data Protection Regulation (GDPR) compliance, particularly due to the immutability of its ledgers and smart contract capabilities. This chapter provides a detailed overview of strategies and best practices for navigating this complex environment while respecting GDPR principles.

Unique Data Processing on Ethereum

Ethereum, thanks to its smart contracts and the EVM (Ethereum Virtual Machine), offers a sophisticated platform for data processing. This unique structure requires special attention to ensure GDPR compliance. Data on Ethereum is immutable once recorded, which raises important questions in terms of the right to be forgotten and modification of personal data.

Pseudonymization and anonymization of data become essential tools in this context, allowing you to benefit from the advantages of blockchain while respecting the privacy of users.

Data Governance and Ethereum

Data governance on Ethereum requires an approach that respects the principles of transparency, accountability and user control set out in the GDPR. Decentralized mechanisms, such as DAOs (Decentralized Autonomous Organizations), offer innovative models for democratic and transparent data governance. These organizations can involve users in decisions related to data management, ensuring processes remain GDPR compliant.

Use of Oracles and External Data Sources

Integrating oracles and external data sources into Ethereum-based applications helps strengthen GDPR compliance by providing verified and up-to-date data. However, this integration must be carried out with caution to ensure that the data collected and used complies with the data minimization and purpose limitation principles of the GDPR.

Smart Contracts and User Consent

Smart contracts on Ethereum enable dynamic and automated management of user consent. This technology offers the possibility of creating systems where users can easily give, modify or withdraw their consent for the use of their personal data. These systems must be designed to be easily understandable and accessible, in accordance with GDPR requirements on informed consent.

Case Studies: Businesses Using Ethereum in Compliance with GDPR

Anonymization of Data in Health Services :

Background : A healthcare technology company has developed an Ethereum-based platform to securely store and share patient medical data.

GDPR approach : Using anonymization techniques to dissociate patient identities from their medical data, while using smart contracts to manage patient consent.

Results : The platform ensures effective protection of patient data, enabling advanced medical research while respecting the GDPR.

Consent Management for Online Services

Background : A digital marketing company implemented a consent management system on Ethereum.

GDPR approach : Smart contracts facilitate transparent and modifiable management of user consent, in line with GDPR requirements.

Results : This system improves user confidence by providing full control over their data, while ensuring company compliance with GDPR.

Payment Solutions and GDPR

Context : A fintech relies on Ethereum to offer decentralized and secure payment services.

GDPR approach : Transactional data is pseudonymized and users have a user-friendly interface to manage their data and consents.

Results : This approach ensures the security of user data and provides a transparent and efficient payment system.

Application of Stealth Addresses on Ethereum for GDPR Compliance

The integration of stealth addresses in Ethereum, a significant advance proposed by Vitalik Buterin, responds to the challenges of transaction confidentiality. These addresses allow anonymous transactions to be carried out, without revealing the addresses of participants on the blockchain, which is crucial for compliance with the GDPR.

Mathematical Formulations for Creating Stealth Addresses

Creating a stealth address on Ethereum can be explained using simple mathematical formulations.

Here is an overview:

1. Key Generation :

o Public key of user B (recipient): PB PB

o Private key of user B: kB kB

o PB=kB×G PB = kB × G (where G G is a generating point on the elliptic curve)

2. Creation of the Stealth Address :

o User A (sender) generates a random number r r .

o It calculates the stealth address: SA=r×G+PB SA = r × G + PB .

o The transaction is sent to SA SA .

3. Discovery of the Stealth Address by B :

o B receives the transaction.

o B calculates r×PB r × PB using its private key kB kB and the point r×G r × G

included in the transaction.

o If r×PB=SA?PB r × PB = SA ? PB , then B knows that the transaction is

intended for him.

4. Confidentiality :

o Only B can determine that the transaction is intended for him, thanks to his

private key.

o Other observers cannot easily link SA SA to B.

This process ensures that each transaction sent to a stealth address is uniquely identifiable to the recipient, thereby preserving confidentiality on the Ethereum blockchain.

Analysis and Discussion: Stealth Addresses and GDPR Compliance on Ethereum

Impact of Stealth Addresses on GDPR Compliance

Improved Privacy :

Stealth addresses increase confidentiality by hiding the real addresses of participants in transactions.

This helps protect personal data, a crucial aspect of GDPR.

Anonymization of Transactions :

By making transactions less traceable, stealth addresses contribute to anonymization, a recognized method for GDPR compliance.

However, anonymization must be robust to comply with GDPR.

Benefits of Stealth Address Integration

Protection of User Identities :

Users benefit from an extra layer of privacy protection, which is especially important in financial transactions.

Potential Compliance with GDPR :

By reducing the amount of personally identifiable data on the blockchain, Ethereum could move closer to GDPR requirements.

Flexibility and Security :

Stealth addresses offer a flexible solution for managing confidentiality without compromising the security inherent in the blockchain.

Challenges and Considerations

Balance between Anonymity and Transparency :

GDPR requires the ability to modify or delete personal data, which conflicts with the immutability of blockchain.

Finding a balance between the anonymity provided by stealth addresses and the transparency necessary for GDPR compliance is complex.

Technical Limitations :

Integrating stealth addresses into Ethereum requires significant technical modifications and community adoption.

Off-Chain Data Management :

Personal data could be managed off the blockchain, but this raises questions about security and centralization.

Conclusion

Potential of Stealth Addresses on Ethereum

Stealth addresses on Ethereum offer considerable potential to strengthen the confidentiality and anonymity of transactions. This feature is particularly advantageous for compliance with the General Data Protection Regulation (GDPR). However, the implementation of these addresses raises notable challenges, particularly in terms of balancing anonymity and transparency, as well as the associated technical constraints. A holistic approach, which takes into account technical and regulatory aspects, is crucial to align Ethereum with the principles of GDPR, while preserving its essential security and decentralization characteristics.

Implications for Investors

For investors, it is essential to understand how companies operating Ethereum approach GDPR compliance. Companies that demonstrate effective and innovative data management on Ethereum position themselves as attractive investment opportunities. They provide a combination of security and compliance, key elements in evaluating investments in emerging technologies.

AI and Innovation in GDPR Compliance

The integration of artificial intelligence (AI) into GDPR compliance strategies marks an important step in innovation and adaptability. Companies that integrate AI-based solutions to comply with GDPR demonstrate an ability to navigate a complex regulatory environment. This adaptability makes them particularly attractive to investors looking to capitalize on companies at the forefront of technology and regulatory compliance.

Summary and Future Perspectives

Using Ethereum in a GDPR-compliant manner is a complex challenge that requires a thorough understanding and strategic application of GDPR principles. Companies that manage to meet this challenge offer promising investment prospects. They combine technological innovation, regulatory compliance and proactive risk management, positioning themselves as leaders in the digital age. By anticipating future developments and adapting to changing regulatory requirements, these companies are charting a path toward a future where blockchain technology and privacy can coexist harmoniously.

References

? PwC Luxembourg. (2018). How Artificial Intelligence helps comply with the GDPR. https://blog.pwc.lu/artificialintelligenceandgdpr/

? MDPI. (2023). Secure Applications with Blockchain and Artificial Intelligence. https://www.mdpi.com/topics/Blockchain_AI

? AI Blockchain Ventures. (2023). Revolutionizing Compliance: How AI and Blockchain Synergy Automates SOC 2, ISO 27001, HIPAA, and GDPR Processes. https://aiblockchainventures.com/Revolutionizing-Compliance

GDPR Compliance as an Investment Criterion

? Data Privacy Manager. (2023). 20 biggest GDPR fines so far [2023].

https://dataprivacymanager.net/5-biggest-gdpr-fines-so-far-2020/

? Porter, A. (2023, August 2). Lessons Learned From GDPR Fines in 2023. CPO

Magazine. Retrieved from https://www.cpomagazi n e.com/data-privacy/lessonslearned-from-gdpr-fines-in-2023/

? McKean, R., Kurowska-Tober, E., Waem, H., & De Souza, R. (2023, January 25). DLA Piper GDPR Fines and Data Breach Survey: January 2023. DLA Piper. https://www.dlapiper.com/en-gb/insights/publications/2023/01/dla-piper-gdpr-finesand-data-breach-survey-january-2023

AI and Data Governance

? Dhanaraj, A. (2023, June 9). Discover How to Navigate Compliance Challenges at the Intersection of Data Governance and AI Integration. Cloud Security Alliance. https://cloudsecurityalliance.org/blog/2023/09/06/discover-how-to-navigatecompliance-challenges-at-the-intersection-of-data-governance-and-ai-integration/

? Tang, A. (2019, October 30). Making AI GDPR Compliant. ISACA Journal. https://www . isaca.org/resources/isaca-journal/issues/2019/volume-5/making-aigdpr-compliant

Data Security and Investment Decision

? IBM. (2023). Research shows extensive use of AI contains data breaches faster and more efficiently. https://www.ibm.com/blog/research-shows-extensive-use-of-aicontains-data-breaches-faster-and-saves-significant-costs/

? Seyfarth Shaw LLP. (2023). Powering Data Breach Response With AI: A Case Study. https://www.mondaq.com/unitedstates/data-protection/875250/powering-data-breachresponse-with-ai-a-case-study

Purposes and Legal Basis of Processing

? Johnson, L., & Brown, S. (2022). “Transparency in Blockchain-based Data Processing: Challenges and Opportunities.” Data Security Review, 16(4), 112-119.

? Smith, J. (2021). “Using AI for Enhanced Data Governance and Compliance Auditing.” International Journal of Blockchain Technologies, 5(2), 58-67.

? Mu?ller, S.C., & Bocek, T. (2019). “AI-Based Compliance Management for Blockchain Systems.” Artificial Intelligence and Law , 27(2), 171-192.

Security Measures and Data Sharing:

? Zhang, Y., Deng, R.H., Liu, X., & Zheng, D. (2019). “End-to-End Encryption in

Blockchain Networks: A Comprehensive Study.” Journal of Network Security , 21(4), 567-584.

? Singh, A., Sharma, N., & Bhushan, B. (2020). “Multi-Factor Authentication in

Blockchain: Enhancing Data Security.” International Journal of Information Security , 19(2), 153-162.

? Chen, L., Lee, WK, Chang, CC, & Choo, KKR (2018). “Blockchain and Smart Contract for Digital Certificate.” IEEE Access , 6, 61903-61917.

? Johnson, S., Mavridou, A., & Laszka, A. (2021). “Smart Contracts for Data Sharing: A Decentralized Approach.” Journal of Blockchain Applications , 3(1), 34-45.

? ReCAPTCHA v2 vs. v3: Effective protection against bots? [2024 Update] -

https://datadome.co/fr/bot-management-protection-fr/recaptcha-v2-ou-v3-protectionefficace-contre-les-bots/

? Crypto Briefing (2019). https://crypto b riefing.com/crypto-captcha-anti-botrecognition/

? Khan, A.N., & Salah, K. (2018). “IoT Security: Review, Blockchain Solutions, and

Open Challenges.” Future Generation Computer Systems , 82, 395-411.

Right of Rectification and Erasure

? Ateniese, G., Magri, B., Venturi, D., & Andrade, E. (2017). Redactable blockchain – or – rewriting history in bitcoin and friends. In IEEE European Symposium on Security and Privacy. https://eprint.iacr.org/2016/757.pdf

? Ashritha, B., et al. (2019). Redactable Blockchain using Enhanced Chameleon Hash Function - https://ieeexplore.ieee.org/document/8728524

? Leclerc, M. (2023) The protection of personal data in the blockchain: issues and perspectives https://www.jeanmougin-avocat.fr/la-protection-des-donneespersonnelles-dans-la-blockchain-jeux-et-perspectives/

? Cai, W., et al. ( 2021 ). Triple‐entry accounting with blockchain: How far have we come? https://researchers.mq.edu.au/en/publications/tripleentry-accounting-withblockchain-how-far-have-we-come

? Zichichi, M., Ferretti, S., & D’Angelo, G. (2020). “How to Forget in the Blockchain: A Privacy Preservation Data Management Framework.” IEEE Access , 8, 124766

Data Breach Management

? Ab Rahman, NH, & Choo, KKR (2017). “A Survey of Information Security Incident Handling in the Cloud.” Computers & Security , 49, 45-69.

Specificities of Ethereum and the GDPR :

? Wirth, C., & Kolain, M. (2018). “Privacy by Blockchain Design: A Blockchain-enabled GDPR-Compliant Approach for Handling Personal Data.” Computer Law & Security Review , 34(2), 304-319.

? Wright, A., & De Filippi, P. (2015). Decentralized Blockchain Technology and the Rise of Lex Cryptographia . SSRN Electronic Journal).

? Tapscott, D., & Tapscott, A. (2016). Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World . Portfolio).

? Christidis, K., & Devetsikiotis, M. (2016). “Blockchains and Smart Contracts for the Internet of Things.” IEEE Access ).

? (Buterin, V. (2014). “A Next-Generation Smart Contract and Decentralized Application Platform.” Ethereum White Paper ).

? Kuo, T.T., Kim, HE, & Ohno-Machado, L. (2017). “Blockchain Distributed Ledger Technologies for Biomedical and Health Care Applications.” Journal of the American Medical Informatics Association , 24(6), 1211-1220.

? Fabiano, N. (2018). “The Internet of Things Ecosystem: The Blockchain and Privacy Issues. The Challenge for a Global Privacy Standard.” International Journal of the Internet of Things and Cyber-Insurance , 1(1), 1-17.

? Casino, F., Dasaklis, T.K., & Patsakis, C. (2019). “A Systematic Literature Review of Blockchain-Based Applications: Current Status, Classification and Open Issues.” Telematics and Informatics , 36, 55-81.

? Tapscott, D., & Tapscott, A. (2017). Blockchain Solutions in Pandemics: A Call for Innovation and Transformation in Public Health . Healthcare Management Forum.

Application of Stealth Addresses on Ethereum for GDPR Compliance

? Buterin, V. (2023). Stealth Addresses for Ethereum. https://vitalik.ca/general/2023/01/20/stealth.html

? Mu?ller, S.C., & Bocek, T. (2019). AI-Based Compliance Management for Blockchain Systems. Artificial Intelligence and Law , 27(2), 171-192.

? Zyskind, G., Nathan, O., & Pentland, A. (2015). Decentralizing Privacy: Using Blockchain to Protect Personal Data. IEEE Security & Privacy Workshops .