In　this　article,　dual-domain　triggered　iterative　learning　control　(ILC)　is　studied　for　networked　switched　systems　against　denial-of-service　(DoS)　attacks.　Unlike　existing　research　on　ILC　focusing　only　on　updating　between　iterations,　a　novel　dual-domain　(time　and　iteration　domains)　triggered　ILC　is　proposed.　The　updates　between　iterations　and　updates　of　network　feedback　information　for　each　iteration　on　the　time　scale　are　performed,　reducing　the　iteration　steps　and　network　data　transmission　frequency　within　each　iteration.　In　each　iteration,　the　system　output　is　transmitted　via　a　network,　which　is　assumed　to　be　vulnerable　to　DoS　attacks.　An　attack　detection　mechanism　and　buffer-based　compensation　mechanism　are　proposed.　Then,　the　boundedness　of　the　iterative　tracking　error　of　the　networked　switched　systems　is　ensured　through　a　switching　stability　analysis　based　on　the　Lyapunov　theory.　Finally,　the　advantages　of　the　proposed　methods　are　substantiated　by　a　simulation　example　consisting　of　three　parts.