Cognitive privacy middleware for deep learning mashup in environmental IoT

Elmisery, A.M. ORCID: 0000-0003-1077-4790, Sertovic, M. and Gupta, B.B., 2018. Cognitive privacy middleware for deep learning mashup in environmental IoT. IEEE Access, 6, pp. 8029-8041. ISSN 2169-3536

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Abstract

Data mashup is a Web technology that combines information from multiple sources into a single Web application. Mashup applications support new services, such as environmental monitoring. The different organizations utilize data mashup services to merge data sets from the different Internet of Multimedia Things (IoMT) context-based services in order to leverage the performance of their data analytics. However, mashup, different data sets from multiple sources, is a privacy hazard as it might reveal citizens specific behaviors in different regions. In this paper, we present our efforts to build a cognitive-based middleware for private data mashup (CMPM) to serve a centralized environmental monitoring service. The proposed middleware is equipped with concealment mechanisms to preserve the privacy of the merged data sets from multiple IoMT networks involved in the mashup application. In addition, we presented an IoT-enabled data mashup service, where the multimedia data are collected from the various IoMT platforms, and then fed into an environmental deep learning service in order to detect interesting patterns in hazardous areas. The viable features within each region were extracted using a multiresolution wavelet transform, and then fed into a discriminative classifier to extract various patterns. We also provide a scenario for IoMT-enabled data mashup service and experimentation results.

Item Type: Journal article
Publication Title: IEEE Access
Creators: Elmisery, A.M., Sertovic, M. and Gupta, B.B.
Publisher: Institute of Electrical and Electronics Engineers
Date: 2018
Volume: 6
ISSN: 2169-3536
Identifiers:
NumberType
10.1109/access.2017.2787422DOI
Divisions: Schools > School of Science and Technology
Depositing User: Jonathan Gallacher
Date Added: 22 Mar 2019 09:43
Last Modified: 22 Mar 2019 09:43
URI: http://irep.ntu.ac.uk/id/eprint/36132

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