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.
翻译:在许多事物( IoT) 互联网应用中, 由 IoT 设备感知的数据被持续发送到服务器, 并按规格进行监控。 由于数据通常包含敏感信息, 且受监控的规格通常是专有的, 两者都必须保持与另一端的私密性。 我们提议一项协议, 进行隐蔽的在线监测 -- -- 在不向对方透露私人信息的情况下进行在线监测 -- -- 违反安全 LTL 规格。 在我们的协议中, 我们首先将安全 LTL 公式转换成 DFA, 并与 DFA 进行在线监测。 基于完全同质加密( FHE), 我们建议使用两种在线算法( 逆向和 Block ) 来运行 DFA 。 我们证明我们整个协议的正确性和安全性。 我们还展示了我们算法在理论上和实验上可以推广的尺度。 我们的案例研究显示, 我们的算法足够快, 来在线监测血糖水平, 并显示我们的协议的实用性 。