With　the　rapid　developments　in　computational　and　communication　resources,　modern　industrial　electronics　systems　can　leverage　networked　structures　to　realize　wireless　remote　control.　However,　owing　to　the　intrinsically　more　open　attributes　of　their　cyberrealms,　an　adversary　could　eavesdrop　on　the　sensitive　information　of　control　systems　to　elaborate　insidious　false　data　injection　(FDI)　attacks,　leading　to　the　destruction　of　safety　performance　at　the　control　systems　level　while　potentially　also　performing　disguising　capabilities　against　traditional　anomaly　detectors.　In　this　article,　we　first　introduce　three　kinds　of　FDI　attack　monitoring　architectures　while　discussing　their　applicability　to　stealthy　corruptions　and　capturing　their　advantages　and　deficiencies.　Then,　we　discuss　the　significant　meanings　of　FDI　attack　monitoring　for　deploying　secure　defense　control,　where　the　interconnections　as　well　as　the　distinctions　between　safety　and　security,　the　methodologies　of　isolation　and　compensation　for　FDI　attack-resilient　control,　and　their　great　potential　of　integration　with　information　security　and　machine　learning　techniques　are　discussed.　Finally,　a　case　study　of　an　autonomous　robot　in　an　industrial　electronics　system　is　performed　to　provide　viewpoints　for　researchers　and　practitioners.　The　purpose　of　this　review　is　to　retrospect　the　representative　results　on　FDI　attack　monitoring　and　control　and　provide　meticulous　insights　to　advance　the　developments　in　safety　and　reliability　of　cyberphysical　systems　(CPSs).