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QoS-aware personalized privacy with multipath TCP for industrial IoT: analysis and design
journal contribution
posted on 2020-06-01, 00:00 authored by Shiva PokhrelShiva Pokhrel, Youyang Qu, Longxiang GaoLongxiang GaoWith the ensuing surge in data communication volume and the growing need for privacy protection, limiting centralized data collection to the minimum required for specific tasks has been mandatory in industries. This is now guided by the modern privacy legislation, namely, the General Data Protection Regulation and the California Consumer Protection Act. Privacy leakage has become increasingly serious because of massive volume and a variety of data transmission and Quality-of-Service (QoS) requirements in the Industrial Internet-of-Things (IIoT) networks. Although differential privacy is the core privacy protection paradigm, most of its extensions assume all parties share the same level of privacy requirements, which cannot meet varying needs and QoS of IIoT devices in practice. In addition, with multiple paths access to the cloud server (often operated by the trusted third party in IIoT) for higher reliability and performance, satisfying both the privacy and QoS is nontrivial during the data transmission. The usual transmission over both the cellular and WiFi interfaces simultaneously for continuous connectivity among devices, edge networks, and the server is crucial. As a result, we observe that IIoT data privacy is highly vulnerable to collusion attacks. Motivated by this observation, we develop a detailed QoS modeling for multipath TCP over IIoT and propose a QoS-aware personalized privacy protection model. Our model works in two different layers: one at the cloud server and another at the network edges (access points/base station). The aim is not only to balance the load but also to achieve the required QoS and optimize the tradeoff between privacy protection and efficiency. The extensive experimental results based on the real-world data sets illustrate the superiority of the proposed model in terms of privacy protection and efficiency.
History
Journal
IEEE internet of things journalVolume
7Issue
6Pagination
4849 - 4861Publisher
IEEELocation
Piscataway, N.J.Publisher DOI
eISSN
2327-4662Language
engPublication classification
C1 Refereed article in a scholarly journalUsage metrics
Keywords
Analytic modelingefficiencyIndustrial Internet of Things (IIoT)personalized privacy protectionQuality-of-Service (QoS) awarenessScience & TechnologyTechnologyComputer Science, Information SystemsEngineering, Electrical & ElectronicTelecommunicationsComputer ScienceEngineeringPrivacyQuality of serviceDifferential privacyServersAUTHENTICATIONAGGREGATIONPROTOCOLINTERNETDistributed Computing
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