Role of Blockchain in Supply Chain

UAE's #blockchain guide outlines several significant challenges facing the widespread adoption of blockchain technology. These challenges include: •Education and Capabilities: There is a lack of fundamental understanding of how blockchain works beyond its association with #cryptocurrency. This lack of awareness extends to lawmakers, hindering the development of constructive regulations. Furthermore, there is a shortage of talented enterprise-level blockchain software developers and a need for proper training programs at various levels. •Interoperability: A major concern arises from the multitude of different blockchain systems that exist, often using different languages, platforms, consensus mechanisms, and protocol schemes. The lack of a standard to ensure compatibility and harmonious operation between these different blockchains poses a significant challenge to the technology's development and adoption . This disconnection can lead to confusion and hesitation among decision-makers. •Scalability: Creating blockchain platforms that can adapt to the growing needs of companies and governments remains a critical challenge. Issues related to implementation, cost, and employee training need to be considered. The inherent technological challenge lies in the fact that every transaction adds a new block, increasing the blockchain's size and potentially leading to performance bottlenecks. Current systems like Bitcoin have significantly lower transaction processing capacities compared to traditional systems like Visa. While solutions like Sharding and off-chain transactions are being explored, no perfect solution currently exists. •Regulatory Clarity: The borderless nature of blockchain networks clashes with the lack of consistent regulatory clarity and differences between jurisdictions. As technology advances faster than regulations, risks and uncertainties persist. Many regulators lack a comprehensive understanding of blockchain and cryptocurrencies, hindering the application of cohesive regulatory approaches. The current cryptocurrency regulations are often inconclusive and scattered, with no unified international standards for cryptocurrencies or data ownership. The UAE's efforts with WEF to establish global standards are a positive step towards addressing this challenge . •Governance: Establishing policies and continuously monitoring their implementation within a blockchain network is complex, especially since it's a relatively new technology with no established "best recipe". The diverging interests of a network's stakeholders as they interact with and derive value from the network further complicate governance. Governments and industries need to be prepared to address change in a way that benefits all stakeholders without compromising the network. This includes decisions on consensus protocol changes, rules for network participation, block size adjustments, and the adoption of off-chain solutions10

Reimagining Compliance, Trust and TPRM: Could Blockchain End Our Reliance on PDFs, Screenshots and Questionnaires? ⛓️ Why not use proof instead of trust. And what if instead of trusting auditors, we also trust math? 🔢 Who trusts Attestations and Certifications? 📋 SOC 2 provides trust. You also require trust. You trust that: - The vendor implemented what they claimed (lol, sure) - The auditor properly validated those claims (with screenshots, of course) - Controls haven't degraded since assessment (infrastructure never changes) - Documentation reflects reality (boilerplate policies FTW) But in security, trust isn't a strategy - verification is. Blockchain Security Validation: Trust the Proof ⛓️ Imagine replacing subjective assessment with cryptographic verification: - Configuration states are validated and cryptographically signed - Results immutably recorded on blockchain, evidence are now tamper-proofed - Smart contracts can validate controls automatically against predefined criteria - You can check historical record showing continuous compliance, - Easy real-time alerting when controls drift from attested state Rather than an auditor telling you that "encryption is used," the system would cryptographically verify that "TLS 1.3 is correctly implemented on all endpoints with no deprecated ciphers." Documentation Theatre to Verifiable Security 🎭 This transforms security attestation from paperwork exercise to mathematical proof: - Customers verify cryptographic evidence instead of reading through lengthy massaged control language - Vendors can prove continuous compliance, not just during audit cycles - Configuration drift triggers immediate alerts, not annual findings - Technical teams focus on implementation, not documentation - Customers can check control effectiveness without seeing sensitive implementation details, preserving vendor confidentiality The blockchain creates a permanent, verifiable history addressing both trust issues and point-in-time limitations of current attestations. Why This Matters 🎯 By bridging the documentation-reality gap with cryptographic proof, we eliminate the need for sample-based shallow testing. Imagine never having to answer "Do you have MFA?" again because customers can verify your MFA implementation themselves. The Path Forward 🚀 This isn't woo-woo - the building blocks exist today. We have: - Secure enclave technologies for sensitive validation - Smart contract platforms for attestation logic - API-driven cloud environments ready for integration - Zero-knowledge proofs for private verification What's missing is standardisation and ecosystem adoption. The first vendor to implement this model won't just streamline compliance/audit - they'll fundamentally change TPRM/customer trust dynamics. PS: This wouldn't work for all controls, lots of legal liability to work through, etc. #GRCEngineering

People hear SOC 1, SOC 2, SOC 3, and ISO 27001 and think they are all the same. They are not. And understanding the difference matters. Because every framework answers a different trust question. SOC 1 asks: Can financial reporting controls be trusted? SOC 2 asks: Can security, availability, confidentiality, processing integrity, and privacy controls be trusted? SOC 3 asks: Can that trust be communicated publicly in a simplified way? ISO 27001 asks: Does the organization have a structured information security management system that continuously identifies, manages, and improves security risks? This is where many organizations get confused. They pursue certification or reports as a checkbox. But the real purpose is not the certificate. The real purpose is assurance. Assurance that controls exist. Assurance that risks are understood. Assurance that evidence can support trust. Assurance that security governance is not only documented, but working. In today’s environment, customers, regulators, partners, and leadership teams do not only want promises. They want proof. That is why frameworks like SOC and ISO 27001 are becoming business enablers, not just audit requirements. Because trust is no longer built by saying “we are secure.” Trust is built by proving it. #CyberSecurity #ITAudit #GRC

🚨 𝐇𝐨𝐰 𝐭𝐨 𝐏𝐨𝐰𝐞𝐫 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 — by DEUNA👇 Modern payments no longer just process — they reason, adapt, and optimize. This post breaks down the architecture of an AI-native payments ecosystem — and how leading enterprises are using it to reduce friction, improve approval rates, and drive intelligent growth. — 𝐓𝐡𝐞 𝐄𝐯𝐨𝐥𝐯𝐢𝐧𝐠 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 AI connects the dots between data, security, speed, personalization, and behavior — enabling intelligent action in real time. 🔹 Security → Real-time fraud scoring and behavioral anomaly detection. Microsoft leverages AI to detect coordinated fraud attacks across geographies, using real-time IP fingerprinting and dynamic 3DS decisions. 🔹 Speed → Automated decisioning and optimized checkout logic. eBay deploys AI models to streamline its global checkout flow, dynamically adjusting the experience by market, device, and payment method trends. 🔹 Personalization → Adaptive routing and dynamic UX. Checkout.com enables merchants to personalize payment options at checkout based on customer history, issuer behavior, and local preferences. 🔹 Behavioral Data → Continuous learning from patterns in issuer behavior, retries, fraud triggers, and consumer habits. — 𝐓𝐡𝐞 𝐂𝐨𝐫𝐞 𝐋𝐚𝐲𝐞𝐫𝐬 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 (hypothetical examples) 1️⃣ Unified Data → Consolidation of data from PSPs (e.g., Getnet, Stripe, Payplug), fraud tools, CRMs, and internal commerce systems. → eBay standardizes transaction-level data across global PSPs and marketplaces to enable unified performance insights and routing logic. 2️⃣ Agentic Intelligence → A reasoning layer that evaluates and ranks millions of routing paths, retries, and fraud strategies based on expected outcome. → Getnet merchants in LATAM use ATHIA to switch routing strategies in real time during issuer outages. 3️⃣ Machine Learning → ML models tailored to commerce — optimizing for approval rates, fraud risk, customer type, and payment method behavior. → Google uses ATHIA’s ML models to proactively adjust retry windows for license renewals based on historical bank acceptance timing. 4️⃣ Analysis & Visualization → Data is transformed into dynamic visualizations that surface anomalies and opportunities without requiring deep SQL or manual dashboards. → Stripe provides merchants with visual routing breakdowns and simulated outcomes — 𝐓𝐡𝐞 𝐎𝐮𝐭𝐜𝐨𝐦𝐞: 𝐀 𝐒𝐲𝐬𝐭𝐞𝐦 𝐓𝐡𝐚𝐭 𝐀𝐜𝐭𝐬 — 𝐍𝐨𝐭 𝐉𝐮𝐬𝐭 𝐑𝐞𝐩𝐨𝐫𝐭𝐬 ✅ Contextual checkout experiences by geography and device ✅ Lower transaction costs via intelligent acquirer routing ✅ Higher approval rates through dynamic retries ✅ Reduced fraud and false declines with adaptive scoring AI in payments is no longer experimental. It’s the backbone of scalable, programmable commerce. Intelligence in motion. — Source: DEUNA ► 𝐓𝐡𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐁𝐫𝐞𝐰𝐬: https://lnkd.in/g5cDhnjC ► Connecting the dots in Payments... | Marcel van Oost

Learning - Network Basics Network Security Basics: 1. Firewalls: The Border Checkpoint A firewall sits at the edge of your network. It inspects every "vehicle" (data packet) trying to enter or leave. It checks the license plate (IP address), the type of vehicle (protocol), and where it’s going (port). The Analogy: Think of a Security Gate at a Military Base. If you don't have the right ID or a valid reason to be there, the gate stays down, and you are turned away. 2. VPN (Virtual Private Network): The Private Tunnel When you drive on a public highway, everyone can see your car and what's inside. A VPN creates an encrypted connection over the public internet. The Analogy: Imagine a Blacked-Out Underground Tunnel built specifically for your car. You enter the tunnel at your house and exit directly at your office. People on the surface highway know a tunnel exists, but they can't see who is inside or what they are carrying. 3. IDS/IPS: The Highway Patrol & Road Spikes IDS (Intrusion Detection System): This is a passive monitor. It watches for suspicious behavior, like a car weaving between lanes or speeding. IPS (Intrusion Prevention System): This is active. It doesn't just watch; it acts. The Analogy: Police Cruisers and Automated Road Spikes. The IDS is the officer with the radar gun who logs your speed. The IPS is the officer who pulls you over or triggers road spikes to stop a high-speed chase before it reaches a crowded city center. 4. Zero Trust: The Constant ID Check In older networking, once you were "inside" the perimeter, you were trusted. In a Zero Trust model, you are never automatically trusted, regardless of where you are. The Analogy: Multiple Internal Security Badging Stations. Even after you pass the main gate of a campus, every single door you walk through requires you to scan your badge again. Just because you are on the property doesn't mean you have the keys to the vault. 5. Encryption: The Locked Armored Truck Encryption scrambles your data so that even if it is stolen, the thief can’t read it without the "key." The Analogy: An Armored Delivery Truck with a Code. If a thief manages to hijack the truck on the highway, they find that all the packages inside are locked in titanium boxes with digital keypads. Without the code, the contents are just useless weight to them. 6. DDoS Protection: Preventing the Traffic Jam A Distributed Denial of Service (DDoS) attack is when a hacker sends so much "fake" traffic to a site that legitimate users can't get through. The Analogy: DDoS attack is a malicious traffic jam where "fake" cars (data) clog the roads to block real people from their destination. DDoS protection acts like a traffic controller that spots the fake cars and diverts them to a side lot (a scrubbing center) so legitimate traffic can keep moving.

Building the Future: The Ethereum L1 + L2 Vision and Enterprise Applications Vitalik Buterin recently shared his vision for the future of Ethereum and blockchain scalability in his blog post “The L1 and L2 Scalability Future”. https://lnkd.in/eS2kVr6e His message is clear: the Layer 1 (L1) and Layer 2 (L2) ecosystem is evolving, not to compete but to collaborate in creating a more robust, secure, and scalable blockchain future. Key takeaways: • L1 for Security and Decentralization: The Ethereum base layer remains the foundation of security and decentralization. • L2 for Scalability and Innovation: Layer 2 solutions enable faster and cheaper transactions, providing the infrastructure for massive user growth and diverse applications. • Enterprise Opportunities: The modular L1/L2 stack creates unparalleled flexibility for enterprises to build blockchain solutions tailored to their needs. How Enterprises Can Leverage This Vision 1. Optimized Costs: Enterprises can utilize L2 solutions for high-frequency, cost-sensitive transactions while benefiting from the robust security of Ethereum L1. 2. Interoperability: L2 networks’ ability to interact seamlessly with L1 opens doors to cross-chain applications, streamlining processes in supply chain management, finance, and beyond. 3. Customizability: Modular L2s allow enterprises to create specific rollups or application chains that meet compliance and privacy requirements without sacrificing scalability. 4. DeFi Access: Companies can now integrate with decentralized finance (DeFi) applications without overwhelming costs, allowing them to unlock new liquidity channels and innovative financial models. 5. Sustainability: With innovations like data compression and zk-rollups, enterprises can lower their carbon footprint while scaling operations sustainably. Why This Matters Now We’re witnessing the maturation of blockchain technology from a niche innovation to a foundational infrastructure layer for enterprises. Whether you’re a global bank exploring tokenization, a logistics company seeking supply chain transparency, or a fintech company looking to tap into decentralized liquidity, the L1 + L2 future makes blockchain adoption more accessible than ever. The convergence of decentralization, scalability, and customizability is not just theoretical—it’s happening now. Enterprises that embrace this future stand to gain a competitive edge in a world increasingly reliant on trustless and transparent systems. What’s your take on the L1 + L2 roadmap? How do you see it transforming enterprise applications? Let’s discuss. #Ethereum #Layer2 #BlockchainForBusiness #Scalability #Innovation Feel free to tweak this as needed! It ties the technical vision into enterprise use cases while staying concise and engaging.

One of the most interesting aspects of my last few roles, including my current work at Humain, is operating at the intersection of AI and advanced security/encryption techniques from zero-knowledge proof systems to the extension of Zero Trust principles into the agentic world. In traditional Zero Trust, we authenticate users and devices. In the agentic world, the “user” could be an autonomous agent — a system that reasons, acts, and interacts with data and other agents, often at machine speed. That changes everything. To secure this new ecosystem, Zero Trust must evolve from static identity verification to dynamic trust orchestration, where every action, decision, and data exchange is continuously verified, contextual, and cryptographically enforced. 1. Agent Identity and Attestation Every agent must have a verifiable, cryptographically signed identity and prove its integrity at runtime; not just who you are, but what you’re running: the model, weights, policy context, and data provenance. 2. Intent-Aware Policy Enforcement Access control must become intent-aware, so agents act only within bounded policy domains defined by explicit goals, permissions, and ethical constraints — continuously verified by embedded governance logic. 3. Least Privilege and Time-Bound Access Agents must operate under least privilege, with access granted only for the minimum scope and durationrequired. In fast-moving agentic environments, time-limited trust becomes an essential safeguard. 4. Assumed Breach and Blast Radius Containment We must assume some agents or environments will be compromised. Security design should minimise impact through microsegmentation, strict trust boundaries, and dynamic reassessment of communication between agents. 5. Encrypted Cognition As models process sensitive data, confidential AI becomes essential where combining homomorphic encryption, secure enclaves, and multi-party computation can ensure that the model cannot “see” the data it processes. Zero Trust now extends into the reasoning process itself. 6. Adaptive Trust Graphs Agents, services, and humans form dynamic trust graphs that evolve based on behaviour and context. Continuous telemetry and anomaly detection allow these graphs to adjust privileges in real time based on risk. 7. Cryptographic Provenance Every output, decision, summary, or recommendation must be traceable back to the data, model, and policy that produced it. Provenance becomes the new perimeter. 8. Autonomous Audit and Forensics Every action should be self-auditing, cryptographically signed, and non-repudiable forming the foundation for verifiable operations and compliance. 9. Machine-to-Machine Governance As agents begin to negotiate, transact, and collaborate, Zero Trust must extend into inter-agent diplomacy, embedding ethics, accountability, and policy directly into machine communication. If you’re working on AI security, agent governance, or confidential computation, I’d love to connect.

Blockchains are permissionless, decentralized, neutral, and immutable...and useless as financial systems of record. Now that institutions are moving onchain, this is a big problem. Blockchains were designed to record only what happened, but financial institutions require clarity on what it means and who is accountable. This creates four gaps that block institutional adoption: 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗴𝗮𝗽. Anyone can deploy a smart contract. Economic meaning splinters across thousands of protocols. A "transfer" on one chain means something different on another. 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗴𝗮𝗽. Ethereum, Solana, and Bitcoin represent the same economic action differently. Field names differ. Transaction formats differ. There's no canonical standard. 𝗦𝗰𝗮𝗹𝗲 𝗴𝗮𝗽. Full history must be preserved and replayed. A simple portfolio query requires parsing years of blockchain data. Most teams underestimate how expensive this gets. 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗴𝗮𝗽. Blockchains record events, but no one is responsible for interpreting them. No one certifies the output. No one stands behind the methodology. For example: in traditional finance, a fund calculates portfolio value by pulling standardized data from Bloomberg or a prime broker. For its onchain portfolio, that same fund must interpret events from dozens of protocols, replay years of history for a single query, and explain the methodology to auditors, without industry-standard definitions or anyone to certify the numbers. This is what we work on every day at Allium: translating raw blockchain events into standardized, finance-ready data, building a true system of record for onchain finance.

🚧 The Tokenisation Boom Is Happening — But Institutional Adoption Isn’t. Why? We talk a lot about tokenisation transforming finance, but a new Singapore–UK joint report shows a harder truth: 👉 Institutions want tokenised assets — but they still can’t actually use them. The gap between what issuers build and what buy-side investors require is wider than most people realise. 🔹 1. The Technology Is Ready — Institutions Are Not Issuers are building fast, but often in “tech-first mode”: • Smart contracts, interoperability, programmable rules… • But not enough integration with portfolio systems, risk tools, or compliance stacks. Institutions can’t allocate without all three. 🔹 2. Liquidity Is the Biggest Barrier Institutions need predictable, deep liquidity — not retail-driven “spikes.” Today’s tokenised markets are: • Fragmented • Shallow • Missing institutional-grade market makers This alone disqualifies many tokenised assets from allocation. 🔹 3. Custody Is the Make-or-Break Issue Traditional custodians aren’t fully ready. Digital-native custodians are ready, but not fully integrated. So institutions face a choice they don’t want: 🟥 Self-custody (operational risk) 🟧 New digital custodians (trust gap) 🟩 Traditional custodians (limited token support) 🔹 4. Regulations Need Harmonisation Even regulators know the frameworks aren’t fully aligned yet. Singapore and the UK are leading (Project Guardian, IF3), but cross-border standards are still forming. Institutions won’t scale until: • Ownership rights • Token vs. unit classifications • Insolvency protections • Smart contract liability …are globally consistent 🔹 5. The Industry Needs a “Buy-Side First” Approach A major message from the report: 💬 Tokenisation thrives only when products are designed for investor reality — not blockchain ideology. That means listening to: • Pension funds • Asset managers • Insurers • Wealth platforms …who need operational certainty above all else. 🔍 What This Means We’re entering a new phase: Tokenisation is no longer a tech experiment — it’s an operational transformation. The winners will be the firms who: ✔ Build with the buy-side ✔ Align with regulators ✔ Deliver liquidity, compliance, and transparency ✔ Create real interoperability with legacy systems This report is one of the strongest frameworks I’ve seen for understanding why adoption is slower than headlines suggest, and what needs to happen next. 🤔 Question for the community What is the single most important unlock for institutional tokenisation? A) Liquidity B) Custody C) Regulatory clarity D) Interoperability E) Tokenised cash rails F) Something else? Would love to hear perspectives — especially from those working in funds, custody, and regulatory strategy. Follow 👉 George Petrovic & comment or share ♻️ if you found this useful. #Tokenisation #DigitalAssets #AssetManagement #DLT #UK #ProjectGuardian #IF3 #Blockchain #InstitutionalInvesting #RWA #CapitalMarkets #Innovation