Blockchain based end-to-end tracking system for distributed iot intelligence application security enhancement

Lei Xu, Zhimin Gao, Xinxin Fan, Lin Chen, Hanyee Kim, Taeweon Suh, Weidong Shi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

IoT devices provide a rich data source that is not available in the past, which is valuable for a wide range of intelligence applications, especially deep neural network (DNN) applications that are data-thirsty. An established DNN model provides useful analysis results that can improve the operation of IoT systems in turn. The progress in distributed/federated DNN training further unleashes the potential of integration of IoT and intelligence applications. When a large number of IoT devices are deployed in different physical locations, distributed training allows training modules to be deployed to multiple edge data centers that are close to the IoT devices to reduce the latency and movement of large amounts of data. In practice, these IoT devices and edge data centers are usually owned and managed by different parties, who do not fully trust each other or have conflicting interests. It is hard to coordinate them to provide end-to-end integrity protection of the DNN construction and application with classical security enhancement tools. For example, one party may share an incomplete data set with others, or contribute a modified sub DNN model to manipulate the aggregated model and affect the decision-making process. To mitigate this risk, we propose a novel blockchain based end-to-end integrity protection scheme for DNN applications integrated with an IoT system in the edge computing environment. The protection system leverages a set of cryptography primitives to build a blockchain adapted for edge computing that is scalable to handle a large number of IoT devices. The customized blockchain is integrated with a distributed/federated DNN to offer integrity and authenticity protection services.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
EditorsGuojun Wang, Ryan Ko, Md Zakirul Alam Bhuiyan, Yi Pan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1028-1035
Number of pages8
ISBN (Electronic)9780738143804
DOIs
StatePublished - Dec 2020
Event19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 - Guangzhou, China
Duration: Dec 29 2020Jan 1 2021

Publication series

NameProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

Conference

Conference19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
CountryChina
CityGuangzhou
Period12/29/2001/1/21

Keywords

  • Blockchain
  • DNN
  • IoT
  • Security

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