Resource Efficient Federated Deep Learning for IoT Security Monitoring

Idris Zakariyya; Harsha Kalutarage; M. Omar Al-Kadri

doi:10.1007/978-3-031-21311-3_6

Resource Efficient Federated Deep Learning for IoT Security Monitoring

Idris Zakariyya^*, Harsha Kalutarage, M. Omar Al-Kadri

^*Corresponding author for this work

Robert Gordon University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (SciVal)

Original language	English
Title of host publication	Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers
Editors	Wenjuan Li, Steven Furnell, Weizhi Meng
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	122-142
Number of pages	21
ISBN (Print)	9783031213106
DOIs	https://doi.org/10.1007/978-3-031-21311-3_6
Publication status	Published (VoR) - 2022
Event	5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with 27th European Symposium on Research in Computer Security, ESORICS 2022 - Copenhagen, Denmark Duration: 30 Sept 2022 → 30 Sept 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13745 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with 27th European Symposium on Research in Computer Security, ESORICS 2022
Country/Territory	Denmark
City	Copenhagen
Period	30/09/22 → 30/09/22

Keywords

Deep Neural Network (DNN)
Distributed machine learning
Edge devices
Federated learning (FL)
Internet of Things (IoT)
Security monitoring

Access to Document

10.1007/978-3-031-21311-3_6

Cite this

Zakariyya, I., Kalutarage, H., & Al-Kadri, M. O. (2022). Resource Efficient Federated Deep Learning for IoT Security Monitoring. In W. Li, S. Furnell, & W. Meng (Eds.), Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers (pp. 122-142). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13745 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-21311-3_6

Zakariyya, Idris ; Kalutarage, Harsha ; Al-Kadri, M. Omar. / Resource Efficient Federated Deep Learning for IoT Security Monitoring. Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers. editor / Wenjuan Li ; Steven Furnell ; Weizhi Meng. Springer Science and Business Media Deutschland GmbH, 2022. pp. 122-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Resource Efficient Federated Deep Learning for IoT Security Monitoring",

keywords = "Deep Neural Network (DNN), Distributed machine learning, Edge devices, Federated learning (FL), Internet of Things (IoT), Security monitoring",

author = "Idris Zakariyya and Harsha Kalutarage and Al-Kadri, {M. Omar}",

note = "Funding Information: Acknowledgment. This work was supported by the Petroleum Technology Development Fund (PTDF), Nigeria. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with 27th European Symposium on Research in Computer Security, ESORICS 2022 ; Conference date: 30-09-2022 Through 30-09-2022",

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isbn = "9783031213106",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Zakariyya, I, Kalutarage, H & Al-Kadri, MO 2022, Resource Efficient Federated Deep Learning for IoT Security Monitoring. in W Li, S Furnell & W Meng (eds), Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13745 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 122-142, 5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with 27th European Symposium on Research in Computer Security, ESORICS 2022, Copenhagen, Denmark, 30/09/22. https://doi.org/10.1007/978-3-031-21311-3_6

Resource Efficient Federated Deep Learning for IoT Security Monitoring. / Zakariyya, Idris; Kalutarage, Harsha; Al-Kadri, M. Omar.
Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers. ed. / Wenjuan Li; Steven Furnell; Weizhi Meng. Springer Science and Business Media Deutschland GmbH, 2022. p. 122-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13745 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Y1 - 2022

KW - Deep Neural Network (DNN)

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KW - Federated learning (FL)

KW - Internet of Things (IoT)

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Zakariyya I, Kalutarage H, Al-Kadri MO. Resource Efficient Federated Deep Learning for IoT Security Monitoring. In Li W, Furnell S, Meng W, editors, Attacks and Defenses for the Internet-of-Things - 5th International Workshop, ADIoT 2022, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 122-142. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-21311-3_6