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Improving Efficiency in Privacy-Preserving Automated Trust Negotiation with Conjunctive Policies

机译:通过联合策略提高隐私保护自动信任协商的效率

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Automated Trust Negotiation (ATN) is an approach to allow two participants to automatically verify whether their policies are consistent with each other or not. During the negotiation process, in order to protect privacy, both participants intend to disclose their credentials and policies as little as possible. A previous work(ATN)[14] successfully negotiates with perfect privacy preservation where post-negotiation, neither credentials nor policies were revealed to each other. Unfortunately, in order to negotiate with policy with l conjunctive "and" conditions, consisting of m credentials it requires a large computation cost which is linear to combination(??, l). In our work, we focus on this problem and establish a new scheme to lower the cost in the conjunctive condition policy so that our protocol require only ml which can highly decrease computation and communication costs. The proposed scheme performs in semi-honest model. The new idea is adding a dynamic secret key to verify which credentials match with the requested policies. We also demonstrate that this new approach can improve the efficiency of the previous one by showing a qualitative evaluation using implementation and analysis of computation and communication cost.
机译:自动信任协商(ATN)是一种允许两个参与者自动验证其策略是否彼此一致的方法。在协商过程中,为了保护隐私,两个参与者都打算尽可能少地公开其凭据和策略。先前的工作(ATN)[14]成功地与完善的隐私保护进行了协商,在协商后,既不会相互透露凭据也不会泄露政策。不幸的是,为了与具有由m个凭证组成的l个联合“和”条件的策略进行协商,它需要大量的计算成本,该成本与combination(Δε,l)成线性关系。在我们的工作中,我们将重点放在这个问题上,并建立一个新的方案来降低联合条件策略中的成本,以便我们的协议只需要ml即可大大降低计算和通信成本。所提出的方案在半诚实的模型中执行。新想法是添加动态密钥,以验证哪些凭据与请求的策略匹配。我们还证明了这种新方法可以通过使用对计算和通信成本的实现和分析进行定性评估来提高前一种方法的效率。

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