The Web3 ecosystem has long been plagued by the pain points of 'difficult verification of behavioral value and high trust costs in the ecosystem'—users' actions such as clicks, invitations, and co-construction often involve 'fake traffic generation' (such as machine-clicks or fake invitations from zombie accounts), making it difficult for ecosystem parties to distinguish the authenticity of actions, leading to misalignment of rewards. At the same time, users' real contributions lack credible proof, requiring the establishment of trust repeatedly when cooperating with merchants and project parties, resulting in low efficiency. Notcoin's breakthrough lies in building a system of 'trustworthy verification of behavioral value + assetization of verification results' based on the trusted technology stack of the TON public chain: through a multi-layer verification mechanism to ensure actions are genuine and effective, and then converting verification results into users' 'on-chain trust assets', allowing real actions to become 'hard currency' within the ecosystem. As of February 2026, Notcoin's false behavior rate dropped from an initial 30% to 8%, and ecosystem cooperation based on trust assets increased by 400%, providing a new path for Web3 to solve 'behavioral fraud and trust deficiency'.
I. Trustworthy verification system for behavioral value: Technology-driven 'real behavior confirmation'
Notcoin does not rely on a single on-chain record to assess behavioral value, but instead employs a **'multi-layer verification mechanism of on-chain contracts + off-chain data + zero-knowledge proofs (ZKP)'** to ensure genuine and effective behavior from the source, with core verification logic divided into three layers:
• First layer: On-chain behavior trajectory recording, locking 'immutable behavior records'
Every action by users (clicks, staking, invitations, etc.) generates a 'behavior trajectory hash', which is recorded on-chain in real-time to the TON sharded chain. The trajectory includes key information such as action time, device fingerprint (non-private information), and associated objects (e.g., the TON address of the invited user), and is bound to the user's TON DID (decentralized identity), making it unalterable or forgeable. For example, a user's click action must meet the basic rule of 'no more than 10 times within 1 minute on the same device, and no high-frequency switching of IP addresses'; after the trajectory is recorded, if a match is detected between the device fingerprint and historical fraud records, the action is directly deemed invalid. By February 2026, through on-chain trajectory recording, Notcoin intercepted machine-generated click actions accounting for 65% of the total false actions, effectively reducing reward waste.
• Second layer: Off-chain multi-source data corroboration, supplementing 'real feedback on behavioral impact'
Introducing third-party data nodes from the TON ecosystem (such as Telegram social data nodes, offline merchant payment data nodes) to obtain 'off-chain impact data' of behavior, corroborating behavioral value. For example, an invitation action must meet the requirement of 'the invited user having at least 5 on-chain transactions or 1 offline payment within 30 days', with data synchronized from Telegram wallet nodes and merchant data nodes to Notcoin's verification contract. If there is only an invitation record but no subsequent active data, the invitation action is valued at only 50%; staking actions must meet the requirement of 'node online rate exceeding 99% during the lock-up period', with data provided by TON infrastructure nodes, and if the online rate does not meet the standard, the value of the staking action is reduced by 30%. By February 2026, through corroboration with off-chain data, Notcoin identified that the proportion of 'invalid invitations' (zombie accounts) was reduced from 22% to 5%, and the matching degree between behavioral value and actual ecological contribution improved by 80%;
• Third layer: Zero-knowledge proof (ZKP) privacy protection, balancing 'verification and privacy'
The privacy data involved in the verification process, such as user device information and transaction records, is processed through TON's ZKP technology for 'privacy computation'—only outputting the result of 'whether the behavior is genuine' to the verification contract, without disclosing specific private information. For example, when verifying whether a user is a genuinely active Telegram user, ZKP only proves 'this user has interacted on Telegram more than 50 times in the past 30 days', without exposing specific chat content or contacts; when verifying offline payment actions, it only proves 'this payment occurred and the amount is compliant', without disclosing merchant names or transaction details. This design ensures the effectiveness of verification while protecting user privacy, with user acceptance of the verification mechanism reaching 94%, far exceeding the 62% of traditional 'full data upload' models.
The multi-layer verification mechanism allows Notcoin's behavioral value judgment to evolve from 'single record' to 'multi-dimensional corroboration'. Data shows that the efficiency of valid behaviors verified through this system, contributing to actual ecological growth (new user retention, merchant turnover, infrastructure stability), is 3.2 times that of unverified behaviors; at the same time, the verification cost accounts for only 5% of the total behavioral rewards, far below the industry average of 15%.
II. Assetization of verification results: From 'effective behavior' to 'on-chain trust certificates'
Notcoin did not treat verification results merely as 'the basis for reward distribution' but transformed them into **'TON trust tokens (TON Trust Token, TTT)'**—these are on-chain trust assets accumulated based on users' real behaviors, containing three core attributes: 'trust level (L1-L5), trust dimensions (traffic trust, infrastructure trust, co-creation trust), and applicable scenarios', which can circulate and be reused within the TON ecosystem, becoming users' 'credit cards':
• Trust levels are linked to the depth of behavioral verification: L1 (basic trust) requires accumulating 100 valid light behaviors (e.g., genuine clicks, compliant shares), L2 (traffic trust) requires 30 valid invitations (the invited user is active for over 30 days), L3 (infrastructure trust) requires 6 months of valid staking (meeting node online rate standards), L4 (co-creation trust) requires 5 accepted ecological suggestions, and L5 (top-level trust) requires leading more than 10 ecological collaborations (e.g., merchant access, cross-chain project linkages). As of February 2026, Notcoin has issued over 8.5 million TTTs at levels L1-L5, of which 22% are trust certificates at L3 and above, corresponding to ecological contributions 7.5 times greater than L1 users.
• Multi-scenario value transformation of trust certificates: TTT is not just an identity marker but possesses actual rights:
◦ User side: TTT at L2 and above can increase DeFi lending limits (30% increase for L2, 200% increase for L5), with a bad debt rate of only 0.4% (compared to 1.8% for ordinary users); users above L3 can unlock offline merchants' 'pay after consumption' rights (limit up to 5000 $NOT), which drove a 65% increase in merchant turnover by February 2026.
◦ Merchant side: Prioritize cooperation with high-level TTT users (e.g., inviting L4 users for brand promotion, conversion rate is four times that of ordinary users). A certain Southeast Asian offline chain merchant screened cooperative users through TTT, reducing promotion costs by 50%, and achieving a new customer repurchase rate of 62%;
◦ Project side: Use TTT to screen seed users (users above L3 level participate in testing, with a retention rate of 70%). A certain GameFi project screened test users through TTT, leading to a TVL exceeding 280 million USD post-launch, far exceeding the expected 120 million USD.
Trust assetization allows users' real behaviors to gain 'long-term credit value'. Data shows that users holding L2 and above TTT have a 6-month retention rate of 78%, which is 3.6 times that of users without TTT; and 75% of users actively optimize their behaviors to improve trust levels, with the proportion of high-value behaviors (e.g., infrastructure, co-creation) increasing from 30% to 68%.
III. Ecological empowerment of the trust network: Reducing collaboration costs and activating ecological synergy
Notcoin's trust assetization does not exist in isolation but constructs a 'low-trust-cost' collaboration network within the TON ecosystem through **'trust certificate interoperability + cross-role collaboration'**, empowering three major ecological roles:
• User collaboration: Trust certificates reduce social costs
Users can quickly establish collaborative trust through TTT without needing to repeatedly verify their identity or capabilities. For example, a user with L3 infrastructure trust teams up with a user with L2 traffic trust to participate in the 'ecological promotion program'; the system directly recognizes both parties' trust levels and automatically allocates the revenue share (60% for the infrastructure user, 40% for the traffic user) without additional negotiations. By February 2026, the volume of user collaborations through TTT reached 1.2 million times, with a collaboration dispute rate of only 0.8%, far lower than the industry average of 8%;
• Users and merchants: Trust certificates simplify cooperation processes
Merchants do not need to review user qualifications and can directly develop cooperation plans based on TTT levels: L2 users can undertake 'local community promotion' (commission 1000 NOT/community), and L4 users can undertake 'regional merchant access' (commission 5000 NOT/merchant). A Latin American merchant alliance connected 200 users through TTT and completed the access of 50 merchants within one month, achieving a cooperation efficiency five times that of the traditional review model.
• Users and project parties: Trust certificates enhance the depth of cooperation
Project parties use TTT as a selection standard for 'core partners': Users above L4 can participate in early project planning (e.g., product feature voting), and L5 users can receive project equity dividends (up to 5%). As of February 2026, there were 35 projects in the TON ecosystem that screened core partners through TTT, with an average cooperation cycle of 18 months, far exceeding the industry average of 6 months, and project iteration efficiency improved by 45%.
The construction of the trust network significantly reduces collaboration costs in the TON ecosystem. Data shows that based on TTT, ecological cooperation reduces communication costs by 60%, shortens cooperation cycles by 40%, and increases the success rate of cooperation from 55% to 92%; at the same time, the scale of the trust economy in the TON ecosystem (based on TTT transactions, cooperation, and services) reached 1.2 billion USD, accounting for 18% of the total ecosystem scale, growing at a rate of 25% per month.
Conclusion
Notcoin's core value lies in addressing the foundational challenges of Web3—'difficulty in discerning the authenticity of behavior and high trust costs in the ecosystem'—with technological means. It does not allow 'real behavior' to only yield one-time rewards but instead transforms it into transferable and reusable 'trust assets', making every genuine contribution from users a 'credit endorsement' within the ecosystem. This model proves that the future ecosystem of Web3 should not be a 'gray area of anonymous fraud' but rather a trustworthy network where 'real actions are rewarded and credible cooperation holds value'.
In the future, with the support of the TON public chain for 'cross-chain trust certificate interoperability', Notcoin's TTT may circulate within the ecosystems of Ethereum, Solana, and others, becoming a universal 'behavioral trust standard' in Web3. If Telegram opens the 'social trust data' interface, TTT may integrate users' social interaction credibility (e.g., community speech quality, content dissemination authenticity), further enriching the dimensions of trust. For the industry, Notcoin provides not only a behavioral verification solution but also a new logic for trustworthiness in the Web3 ecosystem based on 'real behavior and trust assets'.
