Anonymization Framework for IoT Resource Discovery based on Edge Centric Privacy Model
Santosh Pattar1, Lakshmi K N2, Rajkumar Buyya3, Venugopal K R4, S S Iyengar5, L M Patnaik6

1Santosh Pattar*, Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India.
2Lakshmi K N, Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India.
3Rajkumar Buyya, Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria.
4Venugopal K R, Bangalore University, Bangalore, India.
5S S Iyengar, Department of Computer Science and Engineering, Florida International University, Miami, Florida USA
6L M Patnaik, Consciousness Studies Program, National Institute of Advanced Studies, Indian Institute of Science, Bangalore, India.

Manuscript received on December 02, 2020. | Revised Manuscript received on December 05, 2020. | Manuscript published on December 30, 2020. | PP: 255-267 | Volume-10 Issue-2, December 2020. | Retrieval Number: 100.1/ijeat.B21091210220 | DOI: 10.35940/ijeat.B2109.1210220
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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
Keywords: Communication is established. The method presented herein