Abstract
As the efficacy of Internet of Things is expeditiously growing, maintaining privacy with respect users and applications has become a significant aspect. Since the data is getting generated at tremendous rate that includes Sensitive data (any data considered as private by the Data-owner) which has to be hidden, especially the data collected from the Crowd-Source. Due to resource-constrained sensing devices, IoT infrastructures use Edge devices for real-time data processing. Protecting sensitive data from malicious activity becomes a key factor, as all the communication flows through insecure channels. To develop security infrastructures for IoT and distributed Edge networks, this article proposes a user-centric security solution. The proposed security solution shifts from a network-centric approach to a user-centric security approach by authenticating users and devices before communication is established. The method presented herein is applied to an amusement park scenario, which is modeled as a typical smart IoT network. Here, data from sensors and social networks can boost smart lighting to provide citizens with an elegant and safe environment. However, it is challenging and infeasible to transfer and process zillions bytes of data using the current cloud-device architecture due to bandwidth constraints of networks, potentially uncontrollable latency of cloud services, and privacy concerns while collecting data from IoT devices. Firstly, a standalone IoT-edge system is developed, and later, an integrated IoT-based edge-cloud system is designed to compare the systems’ effectiveness. The implementation results show a close correlation between the standalone edge and dual mode edge system. However, the edge-cloud system provides more flexibility and capability to counter the sensitive data streaming and analytics services within the constrained IoT framework. In this paper we have developed a system that uses fog computing approach to perform various tasks and filters the sensitive data, thus helps in preserving privacy.
Highlights
Internet of Things (IoT) is a vast collection of things, human beings, sensors, and other physical objects that are connected over a network which accredits exchange of information among objects and enables for some action to be taken by these things based on the decision or knowledge obtained from the data collected through the devices [1]
Data collected from an IoT ecosystem contains sensitive data that includes any identity related information like name, address, age, salary, location etc. that has to be accessed based on the considerations of accountable, fair and lawful processing, security safeguards, limited and controlled disclosures, transparency, choice and individual participation, collection and purpose limitations
The data collected by the various sensors that are embedded into numerous objects includes personal data which users does not want to share among the IoT devices, applications and other users [2]
Summary
Internet of Things (IoT) is a vast collection of things, human beings, sensors, and other physical objects that are connected over a network which accredits exchange of information among objects and enables for some action to be taken by these things based on the decision or knowledge obtained from the data collected through the devices [1]. Data collected from an IoT ecosystem contains sensitive data that includes any identity related information like name, address, age, salary, location etc. The privacy solution is applicable only for the video data and in IoT the data is in variety of format collected by the sensors like location, time, temperature, body movements etc. The physical subsystem further comprises of an IoT sensor layer and various stakeholders viz. Data manager, cloud, user and privacy policies, and the cyber subsystem comprises of two layers: edge and Cloud. Whereas the cyber subsystem employs the data acquired by the IoT sensors and edge devices from physical subsystem and facilitates the various data analytics processes through the local cloudlets. 1) To develop and implement an ideal IoT-based edge-cloud system to provide real-time sensitive data streaming and analytics service.
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