Sybil Resistance
In web3, incentive programs are crucial for growing your community and rewarding users. However, they can be targets for Sybil attacks, where malicious individuals create multiple identities or use bots to steal rewards. With Fuul's Sybil Resistance tools, you can allow only legitimate users to receive rewards, protecting your budget and maintaining the integrity of your project.
How does Fuul prevent Sybil Attacks?
Fuul uses proprietary software to defend your incentive program against Sybil attacks at both preventive and proactive levels.
Preventive: Implement payout caps to limit excessive rewards and protect your budget.
Proactive: Detect self-referrals and wallet clusters by analyzing both frontend and onchain data.
Behavioral Cluster Detection
Fuul leverages a proprietary ML model that analyzes 30+ onchain behavior signals to detect clusters of wallets likely operated by the same user. While detection heuristics are not made public, some of the signals we monitor include funding sources, common transactions, among others.
How It Works: If suspicious activity is detected, wallets can be automatically disqualified from receiving rewards.
Self Referral Detector
Fuul leverages software to understand if users are self-referring themselves to different wallet addresses.
Bot Activity Detector
Automated tools are used to gain the system. The Bot Activity Detector identifies when automated tools are used for transactions or interactions and allows blocking those actions.
How It Works: Fuul detects automation software, filtering bot-generated conversions to make sure they do not receive rewards.
Payout Caps
You can limit the maximum amount of rewards to be collected by users.These payout caps can be applied to discretionary time windows (for example, a 100 dollar monthly cap).
Maximum amount an end user can earn from the incentive program.
Maximum amount a referrer can earn in total from their referrals.
Total maximum a wallet can earn, whether from referrals or as an end user.
Why It’s Important to Protect Your Incentive Program
A good incentive program helps attract users and grow your community. But without proper protection, it can be abused, causing financial loss and damaging trust.If projects don’t take Sybil detection seriously, it’s the end users who end up paying the price, as their rewards and experience are affected.
Results & Reporting
Fuul's Sybil resistance system undergoes a thorough validation process. When accounts are flagged as potentially fraudulent, they are subjected to a detailed review to identify any signs of abuse.
Our reports clearly outline the Sybil accounts detected by our tools, giving you confidence in identifying the genuine users who are truly interested and active in your program. Any suspicious activity detected is excluded from the final reward calculations.
Continuous Monitoring
Reward distribution is not a one-time event; it requires continuous monitoring based on real-time metrics. As our models gather more data and adjust, we anticipate improvements in accuracy.
Integrating Fuul's advanced Sybil resistance tools into your incentive programs is a big step towards creating a secure and trustworthy environment for user engagement. With ongoing updates based on real-time data and changes in the web3 landscape, our system is built for continuous improvement. This commitment to fair reward distribution not only strengthens the credibility of your programs but also sets a new standard in the industry. As we move forward, we will keep focusing on refining our strategies to ensure a strong, competitive, and fair ecosystem for everyone.
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