With the rise of cybercrime, threats, fraud and asset breaches, organizations are playing a critical role in protecting sensitive data, securing IT and operational infrastructure, and protecting corporate identities. Many enterprise IAM leaders and IT professionals are questioning the relevant benefits and DLT risks and consensus technologies:
Can identity and access controls be securely managed on DLT?
How does distributing consensus or user verification increase security?
How are relationships verified across multiple parties?
How do existing identity standards coexist with blockchain and industry regulations?
How complex are we creating it, particularly across mobile devices and IoT environments?
How do we encode trust without compromising privacy?
14 applications and implications to consider
The problems with using DLT in IAM processes include technical, legal, business, and cultural implications. These implications should be the foundation of the decision-making process for any architecture investment that supports IAM. Consider the following 14 implications when evaluating where and how DLT can improve an organization’s IAM infrastructure and end-user experience.
1. Centralized vs. decentralized
Organizations are used to proprietary, centralized data storage infrastructure that effectively creates a honeypot for theft, security breach, hacking, fraud, and loss. This model exacerbates the power imbalance between identity card holders and those who choose to use them, including the end user. Distributing identity Verification and governance promise various individual and institutional efficiencies and benefits, but run counter to the status quo of centralization.
2. Public vs. private
Authorized blockchain architectures are an important consideration as few business use cases can be fully public. Instead, use cases require confidentiality and permissions to read and write on a managed blockchain with known participants. This distinction has several other implications for security, computation, and scalability.
3. Dynamism
Access levels, permissions and restrictions change as well as identifiable attributes. DLT must be able to accurately handle the frequency and complexity of inspections in various connectivity and IoT environments with minimal latency.
4. Speed
The consensus algorithms used for verification and distributed access influence the speed and processing power required for the scalable and sustainable delivery of SLAs. These limitations drive R&D on blockchain for IAM and are an integral part of the scope of the implementation.
5. Portability
The digital identity functions must be portable. Blockchain designs can ensure that personal data, auditability, and adequate controls follow users as they move from one organization to another. These designs can be customized to facilitate this process in a timely manner.
6. Privacy
Organizations that collect large amounts of personally identifiable information (PII) face new and evolving risks, regulations, privacy-driven competition, and growing consumer distrust. Leverage DLT-enabled cases like sovereign identity and data minimization through techniques like zero-knowledge evidence that provide stronger data protection. Because PII was replicated and stored in hundreds of organizations, information and sharing controls could remain with the end user.
7. Standards
There are many standards of identity and authentication, including roles, attributes, keys, and rights. These often have to meet non-existent standards for blockchain technologies and cross-chain interoperability.
8. Interoperability
Moving from a centralized to a distributed paradigm requires interconnectivity and coordination of data, API, systems and governance. This is not only happening in large organizations with increasingly diverse IT and OT environments and assets, but also in other organizations and ecosystem partners.
9. Regulatory compliance
Regulations surround people’s data, from the mosaic of international, federal and state privacy laws to specific areas like biometrics, all of which are relevant to IAM and blockchain architecture decisions. For example, GDPR’s right to be forgotten enables citizens to have their personal information erased — A concept that is inconsistent with the immutability of the PII record in a database.
10. Immutability
Immutability -The inability to delete records on a ledger is beneficial for security, but it can compromise the privacy of the PII, determining what information is in the chain or determining what information is in the chain or not Remaining out of the chain is important for other criteria on this list. The immutability of the chain must balance the requirements and safeguards between the parts.
11. Key lifecycle management
To ensure that a person has the correct cryptographic keys for each task at all times, access must be renewed, revoked, and updated. This is a unique IAM requirement that DLT must consider when designing.
12. Usability
Distributed or centralized, IAM UX is the interface between digital identity, personal identification and control mechanisms for personal data. While successful IAM architectures hide complexity from the end user, IAM-UX designers cannot overlook the importance of the user interface for education, consent, usability, and accessibility.
13. Emerging data sets
As data sets are generated and used on a larger scale, leading IAM companies in the fields of biometrics, emotion, and genomics, for example, need to consider current and long-term risks and compliance issues. They should focus on data minimization and privacy engineering techniques.
14. Emerging technologies
New capabilities, designs and best practices are continuously shifting the IAM landscape — not to mention breakthrough developments in blockchain, cryptography, artificial intelligence, cybersecurity, cloud computing, quantum computing, and critical concepts like digital wallets. All of this needs to be taken into account during design and after implementation.
IAM plus DLT
As with any new technology, companies must first define the problem; However, IAMDLT decisions are not just another IT due diligence exercise, as topics such as surveillance capitalism, power dynamics, geopolitical threats, sustainable business models, and human rights underpin digital identity models, the IAMDLT opportunity has an impact on people, institutions and the economy.
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