Sybil Attack

to be continued.

To engage global users, Tlock is going to reward content creators, likers and commenters with certain amount of TOK per action, For example 100 TOK for 1 comment. Then the smart guy Bob sees an opportunity, he created 100 different addresses and used them to post comments, thereby accumulating 10,000 TOK, which is also know as Sybil Attack, this could destroy Tlock's economy.

Obviously, we need to reward content creators fairly, and it should be a decentralized and permanent system to support our vision and satisfy users’ need. Also, it is the key tool in migrating users from traditional Web2 platforms to Tlock.

On-Chain Reputation System

As a solution, Tlock introduces an on-chain reputation system designed to mitigate the impact of Sybil attacks.

Reputation Levels

  • New users start at level 0

  • After human verification, users are elevated to level 1

  • Higher levels are achieved by accumulating scores from others' interactions with your content

Reward Rates

Users are assigned different reward rates based on their reputation levels according to below calculation.

Raten=2(n1)/100Rate_n=2^{(n-1) }/100
Reward=RatenRewardBaseReward = Rate_n * RewardBase

when reputation level is larger than 7, your reward rate will be capped at 100%.

Score Accumulation

The way to upgrade your reputation level is to accumulate sores from others’ commenting or liking.

Score=5(n1)Score = 5 ^{(n-1)}
ScoreTotal=1iScoreScoreTotal = \sum_{1}^{i} Score

A comment from a level 9 user grants a score of 390,625.

Reputation Level Upgrades

Once your reputation sore reach below threshold, your reputation level can be upgraded automatically.

ScoreLeveln=10005(n2)ScoreLevel_n= 1000*5^{(n-2)}

Reputation Propagation

  • Alice has a reputation level of 10, then she comments on Charlie’s post, Charlie receives a score of 1,953,125 immediately.

  • If Charlie was initially at Level 1, this single comment would elevate his reputation to level 6.

  • This system will ensure good users automatically identify and verify another good user to mitigate the impact of Sybil Attack from long term perspective.

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