论文标题
通过完全同型加密，忽略的在线监视安全LTL规范
Oblivious Online Monitoring for Safety LTL Specification via Fully Homomorphic Encryption
论文作者
论文摘要
在许多物联网（IoT）应用程序中，通过物联网设备感知的数据连续发送到服务器并根据规范进行监视。由于数据通常包含敏感信息，并且受监视的规范通常是专有的，因此两者都必须从另一端保持私密。我们提出了一项协议，以进行在线监控 - 在线监控，而无需透露彼此的私人信息 - 针对安全LTL规范。在我们的协议中，我们首先将安全LTL公式转换为DFA，并使用DFA进行在线监控。基于完全同态加密（FHE），我们提出了两种在线算法（反向和块），以运行DFA。我们证明了整个协议的正确性和安全性。我们还从理论和经验上显示了算法的可扩展性。我们的案例研究表明，我们的算法足够快，可以在线监测血糖水平，这证明了我们的协议的实际意义。
In many Internet of Things (IoT) applications, data sensed by an IoT device are continuously sent to the server and monitored against a specification. Since the data often contain sensitive information, and the monitored specification is usually proprietary, both must be kept private from the other end. We propose a protocol to conduct oblivious online monitoring -- online monitoring conducted without revealing the private information of each party to the other -- against a safety LTL specification. In our protocol, we first convert a safety LTL formula into a DFA and conduct online monitoring with the DFA. Based on fully homomorphic encryption (FHE), we propose two online algorithms (Reverse and Block) to run a DFA obliviously. We prove the correctness and security of our entire protocol. We also show the scalability of our algorithms theoretically and empirically. Our case study shows that our algorithms are fast enough to monitor blood glucose levels online, demonstrating our protocol's practical relevance.
