Inside InterLink: A Closer Look at the Human-Verified Blockchain System | BSCN (fka BSC News)

InterLink has emerged as a blockchain project focused on verifying human identities through facial scanning and liveness detection. Launched by InterLink Labs, the network aims to create a decentralized system where each participant is confirmed as a unique person, addressing issues like bot interference and sybil attacks in Web3 environments. The project secured $20 million in seed funding earlier this year, backed by investors including Google for Startups and Monad. As of date, it reports over 2.5 million verified users, marking steady growth since surpassing one million registered scans in June. This expansion reflects ongoing efforts to build a global user base, though the platform remains in its early stages.

The Core Vision: A Network for Real People

InterLink positions itself as a foundation for a "Human Network," where verified individuals form the backbone of the system. The project's whitepaper outlines a goal of reaching one billion active participants, emphasizing applications in identity, governance, and economic coordination. Users become "Human Nodes" after a one-time verification process, which binds their identity to the network without requiring personal data storage on-chain.

This approach differs from typical blockchains, where anonymous wallets can be multiplied easily. Instead, InterLink enforces a one-person-one-identity model. Developers can integrate this via the Human Auth SDK, allowing external platforms to verify users without accessing raw biometric information. The vision extends to distributing rewards through a form of universal basic income funded by AI, though details on implementation remain conceptual at this point.

The network's structure includes modular components: an identity layer, application interfaces, and a blockchain for token management. It seeks to enable fair participation in areas like airdrops and staking, where fake accounts often skew outcomes.

InterLink Human Network## Key Elements: InterLink ID and Human Nodes

At the heart is InterLink ID, a biometric-based verification system. Users scan their face via the app, and AI algorithms check for liveness to prevent spoofs like photos or videos. Once verified, the ID grants access to ecosystem features and turns the user into a Human Node.

Human Nodes replace traditional mining hardware with human participation. No specialized equipment is needed; rewards come from staying active and contributing, such as engaging with mini-apps or sharing resources. The system uses proof-of-personhood, distributing tokens based on verification and activity levels. This method aims for lower energy use compared to proof-of-work models.

Nodes earn InterLink tokens ($ITL or $ITLG), with rewards tied to presence and tasks. Inactive nodes face penalties, including token burns, to maintain network health. A recent DAO vote approved this mechanism, with 72% support from the community. It burns pending rewards exponentially for dormant nodes, potentially disconnecting them if balances hit zero.

The InterLink App and Broader Ecosystem

The InterLink App serves as the main entry point. It handles ID management, token tracking, and access to mini-apps in categories like social, gaming, and finance. Users can contribute to AI training by completing tasks or sharing device computing power, all while keeping data private. A dashboard tracks these contributions, offering transparency.

Developers use the Mini-App Development Kit (MDK) to build and deploy apps. The marketplace allows direct publishing without centralized approvals, contrasting with traditional app stores. Integration tools like the InterLink SDK support iOS, Android, and web, with grants available—up to 500 million $ITL—for AI-focused projects.

Beyond the app, InterLink explores hardware with HumanPad, a wearable device for verification in regions lacking high-quality cameras. Sized like an iPod Shuffle, it focuses on biometrics and could enable financial access for unbanked populations. The ecosystem also includes DeFi elements: a non-custodial wallet, QR payments converting crypto to fiat, and exchanges for spot trading, bridging, and perpetuals with leverage.

Technical Underpinnings: Biometrics, Privacy, and AI

InterLink's technical foundation relies on advanced biometrics for identity verification, combined with robust privacy measures and AI-driven processes to ensure security and scalability. The system starts with facial recognition, using deep learning models like convolutional neural networks (CNNs) and vision transformers (ViTs) to analyze user scans. These models, inspired by architectures such as XceptionNet and EfficientNet, are trained on vast datasets of real and synthetic images. They detect subtle signs of fakes, like unnatural skin textures or irregular blinking patterns.

For a sequence of facial frames, the detection model calculates an authenticity probability, essentially scoring the input from 0 (likely synthetic) to 1 (authentic). This involves spatial analysis of individual images and temporal checks across frames, using optical flow to measure movement consistency—lower coherence often flags deepfakes, as AI-generated content struggles with natural dynamics. Spectral analysis further examines frequency patterns in the images, revealing artifacts common in fakes. The model refines itself by minimizing errors through a binary cross-entropy loss function, which compares predictions against true labels.

Liveness detection adds another layer, requiring users to perform actions like smiling or blinking to confirm real-time presence. This counters static images or pre-recorded videos by monitoring physiological signals, such as eye movements or micro-expressions. All processing happens locally on the user's device to minimize risks, with only encrypted features sent for verification.

Privacy is central, addressed through encrypted biometric data. Raw inputs, like facial scans, are transformed into feature vectors using models like ResNet or ViTs. These vectors undergo salting and random projection hashing to decorrelate components, followed by locality-sensitive hashing to create binary codes that allow matching without revealing originals Zero-knowledge proofs (ZKPs) then commit these hashes using schemes like Pedersen commitments, where a value is hidden but provable. During verification, users generate proofs showing matches without exposing data, stored in a decentralized node pool.

AI enhancements bolster this: self-supervised learning extracts features without labels, differential privacy adds noise to prevent reconstruction, and generative adversarial networks (GANs) test against spoofs. The result is irreversible, cancelable encryption—if compromised, users can re-enroll with a new transformation. This design complies with GDPR and CCPA by minimizing data exposure and decentralizing storage, reducing breach risks. It enables applications in finance for secure onboarding, healthcare for patient verification, and government services like voter checks.

ZKPs underpin much of this, allowing proof of statements without revealing details. They satisfy completeness (true statements convince verifiers), soundness (false ones rarely do), and zero-knowledge (no extra info leaks). The protocol involves commitment, challenge, response, and verification steps. In InterLink, users prove attributes like age on-chain via zk-SNARKs or zk-STARKs, which offer succinct proofs and post-quantum security. Challenges include computational overhead, addressed by optimizations, and trusted setups, avoided with STARKs.

Federated learning trains AI models across devices without centralizing data. In training, devices compute updates using secure embeddings—irreversible representations of biometrics—and send only gradients to an aggregator, which averages them to update the global model. This optimizes a loss function across distributed samples, with convergence guarantees. Techniques like model pruning reduce overhead for mobile devices, and users opt-in during idle times, earning rewards. Backup mechanisms replicate encrypted data across nodes, with real-time monitoring and failover for resilience.

In inference, local devices process new scans into embeddings and run the model for predictions, like authenticity scores, keeping data private. This yields low latency, scalability, and robustness, with metrics showing false acceptance below 0.001 and rejection under 0.005. Compared to centralized systems, it improves fraud detection by 20% through diverse data. Incentives, based on sample size and time contributed, have increased participation by 40%.

Overall, these elements create a multi-layered defense. Performance exceeds 90% accuracy on benchmarks, with federated updates ensuring adaptation to new threats. While vulnerabilities exist, the combination raises attack costs significantly, positioning InterLink as a scalable identity framework.

Token Economy and Financial Structure

InterLink employs a dual-token economy with $ITL and $ITLG, designed to separate utility from investment while supporting compliance and ecosystem growth. $ITL has a total supply of 10 billion tokens, managed by the InterLink Foundation as a strategic reserve. Half of this—5 billion—is allocated for $ITLG holders, with the rest aiding institutional growth and stability. This token focuses on broader network support, such as funding developments and partnerships.

$ITLG, with a 100 billion supply, represents active human participation. Eighty percent is designated for Human Node miners, rewarding verified users for network contributions like activity and resource sharing. The remaining 20% funds incentives, including grants for developers and community programs. Holders can earn $ITL simply by holding $ITLG, without needing conversions, fostering long-term engagement.

$ITL vs $ITLG (InterLink X)This model draws from crypto practices where one token acts as a security for investment, aligning with SEC regulations, while the other powers daily operations. It aims for balance: $ITLG drives user involvement in mini-apps, payments, and launchpads, while $ITL provides backing for expansion. No direct swaps between tokens exist, emphasizing distinct roles.

The structure supports DeFi components, like the ITLX Exchange for spot swaps, cross-chain bridges, and perpetual trading with up to 100x leverage. QR payments allow crypto-to-fiat conversions, easing merchant adoption. Recent clarifications in the project's documentation highlight this separation to ensure regulatory adherence, with $ITLG positioned for real-world uses like aid distribution in unbanked regions.

Allocations encourage inclusivity, with mining rewards based on proof-of-personhood rather than hardware. This ties into the broader vision of AI-funded UBI, where tokens distribute value to verified participants. While specifics on vesting or burns evolve, the economy prioritizes fairness, with community governance influencing adjustments.

Roadmap: From Launch to Global Scale

InterLink's five-year plan starts with core products in 2025: ID, app, chain, SDK, wallet, and exchange. It targets 10 million verified users, NIST-top facial models, and token listings on major exchanges. An InterLink Card for payments aims to reach three million users.

By 2026, focus shifts to AI agents, proprietary LLMs, and developer communities. Preparations for a U.S. stock exchange listing include audits and SEC compliance. Token expansion eyes tens of millions via UBI initiatives across 180 countries.

From 2027 onward, goals include one billion users, positioning as a top mini-app network, and $ITLG as a payment standard for aid in underserved areas. Infrastructure aims to handle 100 billion verifications, replacing traditional KYC methods.

Recent milestones include partnerships with Google and AWS, and community campaigns like bounties and video contests to boost engagement. The project emphasizes listening to feedback, with updates like chat features for real-time interaction.

Frequently Asked Questions (FAQ)

What is InterLink?

InterLink is a blockchain network that verifies real human users through biometric facial scans and liveness detection, preventing bots and duplicate accounts.

How does InterLink verify identities without storing personal data?

InterLink uses encrypted feature vectors, zero-knowledge proofs, and federated learning to verify users while keeping biometric data private and off-chain.

What is the role of Human Nodes in InterLink?

Human Nodes are verified users who earn tokens by staying active and contributing to the network instead of using mining hardware.

What’s the difference between $ITL and $ITLG tokens?

$ITL supports network growth and compliance, while $ITLG rewards user participation. They have separate functions and cannot be swapped directly.

Looking Ahead

InterLink addresses real issues in digital trust, from bots to privacy. Its human-centric design could support fairer Web3 applications, but scaling biometrics globally involves hurdles like device access and regulatory variances. The ambitious targets—one billion users—will test execution.

As blockchain evolves, projects like this highlight shifts toward verified participation. Readers interested in joining can download the app or explore the whitepaper for details. Whether it reshapes identity in Web3 remains to be seen, but the framework provides a structured path forward.

Sources:

1. InterLink Official Whitepaper – Detailed explanation of InterLink’s proof-of-personhood model, technical implementation, and ecosystem components.
2. InterLink Labs Confirms Strategic Investment from Google – Yahoo Finance
3. InterLink Labs Funding Insights – Cryptorank