Swarm-Consensus Defense Achieves 98.2% Against Cloud-LLM Adversarial Attacks
A swarm-consensus defense system demonstrated 98.2% effectiveness against adversarial attacks on cloud-based large language models. The system used a five-defender consensus approach and an autohealer, achieving full defense by round 400 after minimal early breaches. Tests were conducted using local Ollama deployment with three cloud attackers and 13 attack categories.
- ▪The swarm-consensus defense achieved a 98.2% success rate against adversarial attacks on cloud-LLMs.
- ▪A five-defender consensus system combined with an autohealer reached 100% defense by round 400.
- ▪Only six breaches occurred in the first 100 rounds, resulting in a 94% initial defense rate.
- ▪The smallest defender model, llama3.2:3b (4-bit), completed 500 rounds without any failures.
- ▪Testing involved 13 distinct attack categories and three cloud-based attackers.
- ▪The system was built using local Ollama deployment for the defender models.
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