期刊
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
卷 19, 期 5, 页码 2952-2964出版社
IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2021.3078520
关键词
Cloud computing; Edge computing; Data centers; Servers; Clocks; History; Synchronization; Fog computing; edge computing; security; IoT; Intel SGX
类别
资金
- Fundao para a Cilncia e Tecnologia (FCT) [2020.05270.BD, PTDC/EEI-COM/29271/2017, Lisboa-010145-FEDER-029271, PTDC/CCIINF/32038/2017, UIDB/50021/2020]
- European Commission [830892]
- Fundação para a Ciência e a Tecnologia [2020.05270.BD, PTDC/EEI-COM/29271/2017] Funding Source: FCT
This article presents the design and implementation of a secure event ordering service for fog nodes. The service leverages a Trusted Execution Environment (TEE) to provide guarantees regarding the order of events, even when fog nodes are compromised.
The edge computing paradigm extends cloud computing with storage and processing capacity close to the edge of the network, which can be materialized by using many fog nodes placed in multiple geographic locations. Fog nodes are likely to be vulnerable to tampering, so it is important to protect the functions they provide from attacks. A key building block of many distributed applications is an ordering service that keeps track of cause-effect dependencies among events and that allows events to be processed in an order that respects causality. This article presents the design and implementation of a secure event ordering service for fog nodes. Our service, named Omega, leverages the availability of a Trusted Execution Environment (TEE), based on SGX technology, to offer fog clients guarantees regarding the order in which events are applied and served, even when fog nodes are compromised. We have also built OmegaKV, a key-value store that uses Omega to offer causal consistency. Experimental results show that the ordering service can be secured without violating the latency constraints of time-sensitive edge applications, despite the overhead associated with using a TEE. Omega introduces an additional latency of approximately 4ms, that contrary to cloud based solutions, allows latency values in the 5ms-30ms range, as required by time-sensitive edge applications.
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