View in EDS HTML Full Text PDF Full Text

Ai-enabled framework for anomaly detection in power distribution networks under false data injection attacks.

Saved in:
Bibliographic Details
Title: Ai-enabled framework for anomaly detection in power distribution networks under false data injection attacks.
Authors: Ahmad, Hasnain1, hasnain.ahmad@kfupm.edu.sa, Mustafa, Ghulam1, gm@pieas.edu.pk, Gulzar, Muhammad Majid2,3, muhammad.gulzar@kfupm.edu.sa, Ahmed, Ijaz3, ijaz.ahmed.1@kfupm.edu.sa, Khalid, Muhammad3,4, mkhalid@kfupm.edu.sa
Source: Artificial Intelligence Review; Nov2025, Vol. 58 Issue 11, p1-38, 38p
Database: Applied Science & Technology Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 187582106
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Ai-enabled framework for anomaly detection in power distribution networks under false data injection attacks.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Ahmad%2C+Hasnain%22">Ahmad, Hasnain</searchLink><relatesTo>1</relatesTo>, <i>hasnain.ahmad@kfupm.edu.sa</i><br /><searchLink fieldCode="AU" term="%22Mustafa%2C+Ghulam%22">Mustafa, Ghulam</searchLink><relatesTo>1</relatesTo>, <i>gm@pieas.edu.pk</i><br /><searchLink fieldCode="AU" term="%22Gulzar%2C+Muhammad+Majid%22">Gulzar, Muhammad Majid</searchLink><relatesTo>2,3</relatesTo>, <i>muhammad.gulzar@kfupm.edu.sa</i><br /><searchLink fieldCode="AU" term="%22Ahmed%2C+Ijaz%22">Ahmed, Ijaz</searchLink><relatesTo>3</relatesTo>, <i>ijaz.ahmed.1@kfupm.edu.sa</i><br /><searchLink fieldCode="AU" term="%22Khalid%2C+Muhammad%22">Khalid, Muhammad</searchLink><relatesTo>3,4</relatesTo>, <i>mkhalid@kfupm.edu.sa</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Artificial+Intelligence+Review%22">Artificial Intelligence Review</searchLink>; Nov2025, Vol. 58 Issue 11, p1-38, 38p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187582106
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10462-025-11318-3
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 38
        StartPage: 1
    Titles:
      – TitleFull: Ai-enabled framework for anomaly detection in power distribution networks under false data injection attacks.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ahmad, Hasnain
      – PersonEntity:
          Name:
            NameFull: Mustafa, Ghulam
      – PersonEntity:
          Name:
            NameFull: Gulzar, Muhammad Majid
      – PersonEntity:
          Name:
            NameFull: Ahmed, Ijaz
      – PersonEntity:
          Name:
            NameFull: Khalid, Muhammad
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 02692821
          Numbering:
            – Type: volume
              Value: 58
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Artificial Intelligence Review
              Type: main
ResultId 1