# Reputation Consensus Mechanism for Blockchain Based on Information-Centric Networking
## 4 Design
### Hybrid Consensus Mechanism
#### 4.2.1 Reputation Consensus Mechanism
#### 5.1.1 Collusion Attacks

Collusion attacks refer to scenarios in which multiple nodes conspire to manipulate the system for mutual benefit. In RepuICN, high-reputation ICN nodes are selected as proposers for checkpoint blocks. Should multiple high-reputation nodes collude, they may attempt to propose invalid checkpoint blocks or manipulate reputation scores. * Invalid Checkpoint Blocks: The validation of checkpoint blocks in RepuICN is conducted independently by nodes randomly selected from the peer-to-peer network based on the RANDAO protocol. The transparency of on-chain data ensures that reputation nodes cannot artificially enhance their blockchain contribution through data fabrication. * Network Contribution Assessment: The evaluation of network contribution relies on objective measurements of network performance and quality of service, with the corresponding data provided by certified third-party institutions. This approach hinders colluding nodes from elevating their reputation scores via data falsification without detection. #### 5.1.2 Sybil Attacks

A Sybil attack involves an adversary creating multiple fraudulent identities to gain undue influence within the network. In the proposed reputation computation model, a time-decay model and a correction mechanism are incorporated, requiring nodes to accumulate and maintain high reputation scores through sustained honest participation. Consequently, attackers are impeded from rapidly establishing numerous fake identities to acquire high reputation scores, as each identity must demonstrate continuous positive contributions. Moreover, the integration of on-chain staking (e.g., the staked amount) imposes significant economic costs on Sybil attacks, necessitating substantial resource investment for each fraudulent node and further elevating the attack's difficulty. #### 5.1.3 Malicious Behavior by Reputation Nodes

Although ICN reputation nodes undergo identity verification by third-party authoritative institutions to ensure a degree of security, high-reputation nodes may still engage in malicious activities, such as proposing invalid checkpoint blocks or attempting to disrupt the consensus process. Such behaviors could adversely affect the system's performance and security. RepuICN employs the following countermeasures:

* Punishment for Dishonest Behavior: Upon detection of malicious actions, the offending node's reputation score is reset to zero, it is added to a blacklist, and its staked funds are confiscated. This stringent punitive mechanism effectively discourages malicious behavior. * Casper FFG Voting Mechanism: In the Casper FFG protocol, checkpoint blocks must be approved by validator votes, and only blocks that obtain a sufficient quorum are ultimately confirmed. Thus, even if a malicious reputation node proposes aninvalid block, it will not be accepted unless the majority of network validators are compromised. * Redundancy and Timeout Mechanisms: To mitigate proposal delays or interruptions caused by malicious nodes, the system incorporates a timeout mechanism and selects alternative proposers from the pool of high-reputation nodes, ensuring the continuity and stability of the consensus process. ### Incentive Analysis

Incentive mechanisms are central to the design of blockchain networks, driving node participation and ensuring long-term stability and fairness. RepuCN, as a reputation-based hybrid consensus mechanism, allows high-reputation ICN nodes to propose checkpoint blocks and receive additional rewards. This section analyzes, from a game-theoretic perspective, how RepuCN ensures long-term participation, maintains fairness, and incentivizes good behavior while deterring malicious actions through economic rewards. According to the implementation standards of Ethereum's Beacon Chain [46], proposers receive 12.5% of the total block reward [47].