Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Secure Network Model against Bot Attacks in Edge-enabled Industrial Internet of Things
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Game Design.ORCID iD: 0000-0003-2525-3074
2022 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 18, no 11, p. 7998-8006Article in journal (Refereed) Published
Abstract [en]

The new Industry 4.0 standard has offered many advantages to the industries improving their production rate since it evaluates novel cutting-edge technologies like Artificial Intelligence, Machine Learning, Cyber-Physical Systems, and Internet of Things to automate manufacturing processes so as to minimize time and economical costs while improving the quality of products. However, this rapid industrial transition carries risks in terms of security and privacy issues that arise. In this paper, we propose a novel secure network model to enhance network security and employees privacy in the Edge-enabled Industrial Internet of Things. Experimental results demonstrate encouraging performance rates in terms of accuracy, precision, recall, fall-out, F-measure, and Matthews correlation coefficient against known and unknown bot attacks.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022. Vol. 18, no 11, p. 7998-8006
Keywords [en]
Botnet, Botnets, Cloud computing, DDoS attacks, Denial-of-service attack, Honeynet, Industrial Internet of Things, Industry 40, Internet of Things, Malware, MitM attacks, Privacy, Security, Servers, Artificial intelligence, Cybersecurity, Embedded systems, Engineering education, Learning systems, Network security, Cloud-computing, DDoS Attack, Denialof- service attacks, Honey net, Mitm attack
National Category
Computer Sciences Computer Engineering Computer Systems Computer and Information Sciences
Identifiers
URN: urn:nbn:se:uu:diva-472773DOI: 10.1109/TII.2022.3162837ISI: 000856145200062Scopus ID: 2-s2.0-85127469557OAI: oai:DiVA.org:uu-472773DiVA, id: diva2:1652120
Available from: 2022-04-14 Created: 2022-04-14 Last updated: 2025-02-18Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Lv, Zhihan

Search in DiVA

By author/editor
Lv, Zhihan
By organisation
Department of Game Design
In the same journal
IEEE Transactions on Industrial Informatics
Computer SciencesComputer EngineeringComputer SystemsComputer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 230 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf