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New framework enhances privacy in multi-agent systems using trust dynamics

Researchers have developed a new framework called Trust-Aware Privacy Control to enhance privacy in multi-agent systems. This framework dynamically adjusts message disclosure based on trust relationships between agents, aiming to protect hidden goals from adversaries. Experiments show that this trust-dependent stochastic policy effectively reduces adversarial goal inference accuracy while maintaining competitive consensus utility. AI

IMPACT Enhances privacy mechanisms in networked systems, potentially improving security for critical infrastructure like healthcare and smart grids.

RANK_REASON This is a research paper published on arXiv detailing a new framework for privacy preservation in multi-agent systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework enhances privacy in multi-agent systems using trust dynamics

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This is a research paper published on arXiv detailing a new framework for privacy preservation in multi-agent systems. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Tobias J. Oechtering ·

    Trust-Aware Adaptive Disclosure for Inference Privacy Preservation in Multi-Agent Networks

    Agent based systems are increasingly deployed in information critical systems including healthcare management systems, and smart grids. In this paper, we consider a multi-agent system where each agent has a latent goal that needs to be kept hidden from observing adversaries. More…