Sybil Attacks

Sybil attacks, a type of network attack, involve creating numerous fake identities to gain influence over the network. In DeAI scenarios, sybil attacks can result in a larger proportion of malicious nodes during model training, increasing the likelihood of successful data or model poisoning.

One effective mitigation strategy involves identifying attacks through the diversity of updates. This approach relies on the observation that targeted attacks often generate similar gradients with less diversity, enabling the detection of anomalous behavior indicative of Sybil attacks.

Moreover, other defense mechanisms against Sybil attacks in network scenarios prove effective in the context of DeAI:

• Trusted certification: Centralized authorities ensure that each entity possesses a certificate for network participation, thereby mitigating the proliferation of fake identities.

• Resource testing: Nodes undergo testing to assess their computing capability and network bandwidth, facilitating the detection of anomalies suggestive of Sybil attacks.

• Economic costs and fees: Introducing fees for participation discourages Sybil attacks by rendering them economically unviable, thereby enhancing the security of the network.