APA APA 7th

Adeleke, P. E., & Lindqvist, D. H. (2026). A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data. SciMatic Journal of Cybersecurity and Digital Forensics, 1(1), 77-84.

MLA MLA 9th

Adeleke, Prof. Emiola, and Dr. Henrik Lindqvist. "A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data." SciMatic Journal of Cybersecurity and Digital Forensics, vol. 1, no. 1, 2026, pp. 77-84.

CHI Chicago

Adeleke, Prof. Emiola, and Dr. Henrik Lindqvist. "A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data." SciMatic Journal of Cybersecurity and Digital Forensics 1, no. 1 (2026): 77-84.

HAR Harvard

Adeleke, P. E. & Lindqvist, D. H. (2026) 'A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data', SciMatic Journal of Cybersecurity and Digital Forensics, 1(1), pp. 77-84.

IEEE IEEE

P. E. Adeleke, and D. H. Lindqvist, "A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data," SciMatic Journal of Cybersecurity and Digital Forensics, vol. 1, no. 1, pp. 77-84, 2026.

VAN Vancouver

Adeleke PE, Lindqvist DH. A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data. SciMatic Journal of Cybersecurity and Digital Forensics. 2026;1(1):77-84.

BIB BibTeX

@article{prof2026,
  title     = {A Novel Anomaly Detection Framework for SCADA Systems using Federated Learning on Multivariate Time-Series Data},
  author    = {Prof. Emiola Adeleke and Dr. Henrik Lindqvist},
  journal   = {SciMatic Journal of Cybersecurity and Digital Forensics},
  volume    = {1},
  number    = {1},
  pages     = {77-84},
  year      = {2026},
}

Cite This Article