IIoT: Traffic Data Flow Analysis and Modeling Experiment for Smart IoT Devices

Akashdeep Bhardwaj, Keshav Kaushik, Salil Bharany (), Ateeq Ur Rehman, Yu-Chen Hu, Elsayed Tag Eldin () and Nivin A. Ghamry
Additional contact information
Akashdeep Bhardwaj: School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248007, India
Keshav Kaushik: School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248007, India
Salil Bharany: Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar 143005, India
Ateeq Ur Rehman: Department of Electrical Engineering, Government College University, Lahore 54000, Pakistan
Yu-Chen Hu: Department of Computer Science and Information Management, Providence University, Taichung City 433, Taiwan
Elsayed Tag Eldin: Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11835, Egypt
Nivin A. Ghamry: Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, Egypt

Sustainability, 2022, vol. 14, issue 21, 1-18

Abstract: The Internet of Things (IoT) has redefined several aspects of our daily lives, including automation and control of the living environment, innovative healthcare services, and much more. Digital IoT devices and sensors, when integrated with home appliances, industrial systems, and online services in the physical world, have brought intense, disruptive changes in our lives. The industry and home users have widely embraced these ‘things’ on the Internet or IoT. However, the innate, intrinsic repercussions regarding security and data privacy are not evaluated. Security applies to Industrial IoT (IIoT) is in its infancy stage. Techniques from security and privacy research promise to address broad security goals, but attacks continue to emerge in industrial devices. This research explores the vulnerabilities of IIoT ecosystems not just as individual nodes but as the integrated infrastructure of digital and physical systems interacting with the domains. The authors propose a unique threat model framework to analyze the attacks on IIoT application environments. The authors identified sensitive data flows inside the IIoT devices to determine privacy risks at the application level and explored the device exchanges at the physical level. Both these risks lead to insecure ecosystems. The authors also performed a security analysis of physical domains to digital domains.

Keywords: IoT security; data privacy; sensitive data; IIoT apps; physical device; IIoT threat model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/21/14645/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/21/14645/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:21:p:14645-:d:965625

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().