Average consensus has significant applications in dynamic load balancing and cooperative control of vehicle formations, where all the agents receive information from neighboring agents via communication network and update their states to achieve an agreement. However, this approach would result in an undesirable disclosure on the initial states of agents to their neighbors. In this brief, we propose an accurate privacy preserving average consensus (APPAC) algorithm, where all the agents independently generate and transmit random numbers based on Paillier cryptosystem to conceal their initial states. Under the proposed APPAC algorithm, the accurate average consensus is indeed achieved. Besides, the necessary and sufficient conditions that initial states can be inferred are also discussed. Extensive simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

中文翻译：

---

准确隐私保护平均共识

平均共识在车辆编队的动态负载平衡和协同控制方面具有重要应用，其中所有代理通过通信网络从相邻代理接收信息并更新其状态以达成一致。然而，这种方法会导致向其邻居泄露代理的初始状态。在这个简介中，我们提出了一种准确的隐私保护平均共识 (APPAC) 算法，其中所有代理基于 Paillier 密码系统独立生成和传输随机数以隐藏其初始状态。在提出的APPAC算法下，确实实现了准确的平均共识。此外，还讨论了可以推断初始状态的充分必要条件。