An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things

被引:0
|
作者
Alsboui, Tariq [1 ]
Al-Aqrabi, Hussain [1 ]
Hill, Richard [1 ]
Iram, Shamaila [1 ]
机构
[1] Univ Huddersfield, Sch Comp & Engn, Huddersfield, W Yorkshire, England
关键词
Internet of Things (IoT); Distributed Ledger Technology (DLT); IOTA Tangle; Masked Authenticated Messaging (MAM); Privacy;
D O I
10.5220/0011056400003194
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In the Internet of things (IoT), security and privacy issues are a fundamental challenge determining the successful implementation of many IoT applications. Distributed ledger technology (e.g., Blockchain) offers a great promise to solve these issues. Blockchain-based solutions support security and privacy, yet they involve significant energy due to mining, low throughput, and computational overhead that is not acceptable for IoT resource-constrained devices. In this paper, we propose a scalable Privacy-Preserving Distributed Intelligence approach (PPDI) by leveraging the IOTA technology. IOTA is an emerging distributed ledger technology that allows for zero fees transactions for the IoT. The proposed PPDI aims to address the privacy issues in the IoT by using the IOTA Masked Authenticated Messaging (MAM) protocol. MAM ensures privacy by encrypting and granting permission to authorized users to access data. This paper presents a healthcare scenario that demonstrate how IOTA MAM can be used to address the privacy issue in the IoT. The experimental results clearly show that the IOTA MAM is a feasible solution that can be used to solve privacy related issues in the IoT domain.
引用
收藏
页码:174 / 182
页数:9
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