Solicited original submissions must not be currently under consideration for publication in other venues. Second Reviews Due/Notification: November 15, 2019Īll original manuscripts or revisions to the IEEE IoT Journal must be submitted electronically through IEEE Manuscript Central. Future perspectives of privacy issues in IoT applications.
Middleware for privacy protection in IoT applications With the recent wave of disruptive technologies, the deployment of the Internet of Things (IoT) is becoming ubiquitous, ranging from common home and.Multiparty access control in edge computing assisted with evolving IoT.Privacy-enhancing cryptographic techniques.Privacy preserving in presence of advanced persistent threats.Privacy preserving solutions for crowdsensing.Privacy protection in edge computing assisted with evolving IoT.Optimization of the utility-privacy tradeoffs.Topics of interest for this special issue include, but are not limited to This special issue focuses on solutions that leverage techniques and insights from the domains of artificial intelligence, edge computing, and big data to resolve privacy and security challenges in distributed edge computing and evolving IoT applications. All papers to be considered for publication in IEEE Internet of Things Magazine must be submitted through Manuscript Central. While privacy preserving has not been the initial focus of traditional data analytics on edge servers, when used in domains such as cyber security, there are incentivized, malicious adversaries present in the system willing to game and exploit edge processing vulnerabilities. This could potentially lead to security/privacy concerns in many participatory and opportunistic crowd-sensing applications, where a large group of individuals having mobile devices capable of sensing and computing collectively share data and extract information to measure, map, analyze, estimate or infer any processes of common interest. For example, data mining on time-series data taken from motion sensors, microphones, and GPS sensors could reveal users' activities, demographics, attributes and daily interactions. Despite this ongoing advancement, there are growing concerns regarding the privacy of data providers when they grant edge applications direct access to their embedded sensors.ĭata mining on genuine data could be harmful to data privacy. Edge servers are now capable of extracting meaningful analytics from IoT nodes, which give insights about unprecedented changes of data-driven economy that finds applications in diverse sectors ranging from smart manufacturing and smart transportation to predictive maintenance and precision healthcare. The IEEE Transactions on Intelligent Transportation Systems (T-ITS) is published monthly. Recent advances in artificial intelligence, edge computing, and big data, have enabled extensive reasoning capabilities at the edge of the network. IEEE Transactions on Intelligent Transportation Systems is a top-ranked publication in the field of ITS.
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