Paper Info
Title
Cerberus: Privacy-Preserving Computation In Edge Computing
Abstract
Edge computing reduces the overhead of data centers and improves the efficiency of data processing. However, traditional cloud data protection mechanisms are no longer applicable to edge devices. Data leakage and other privacy issues may occur when computation is outsourced to edge nodes. The decentralization raises new privacy challenge for data control, storage and computation. In this work, we present Cerberus, a brand-new framework that preserves data privacy in edge computing by combining blockchain, distributed data storage and trusted execution environment (TEE). Blockchain is used to maintain a global computation state, and also acts as a medium of information interaction. Distributed data storage provides a secure and large-capacity storage. TEE-based off-chain computation guarantees confidentiality and efficiency of data processing. We also implement a prototype of Cerberus using Hyperledger Fabric and Intel SGX. Our evaluation on a sample of data sorting application shows that Cerberus achieves significant speed ups over previous cryptographic schemes. Compared with non secure computation, Cerberus can preserve data privacy without incurring much performance loss.
Year
DOI
Venue
2020
10.1109/INFOCOMWKSHPS50562.2020.9162942
IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)
Keywords
DocType
ISSN
Edge Computing, Data Privacy, Blockchain, Distributed Data Storage, TEE
Conference
2159-4228
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Dilu Zhang100.34
Lei Fan2507.85