The　wireless　sensor　network　(WSN)　is　a　multi-hop　wireless　network　that　comprises　multiple　sensor　nodes　arranged　in　a　self-organized　manner.　It　is　usually　deployed　in　unattended　areas　where　sensor　nodes　can　easily　be　infiltrated　by　attackers　who　can　affect　the　detection　results　by　injecting　false　data.　This　paper　proposes　a　malicious-node　identification　method　based　on　correlation　theory　that　prevents　fault　data　injection　attacks.　First,　anomalies　among　similar　types　of　sensor　data　are　detected　based　on　time　correlation.　Second,　malicious　nodes　are　identified　based　on　spatial　correlation.　Third,　the　identified　malicious　nodes　are　verified　based　on　event　correlation.　The　experimental　results　and　their　comparison　with　those　of　existing　methods　show　that　the　proposed　scheme　has　better　recall　with　lower　false-positive　and　false-negative　rates　than　those　of　the　traditional　fuzzy　reputation　model　and　weighted-trust-based　methods.　(C)　2021　The　Authors.　Published　by　Elsevier　Ltd.