The　frequent　occurrence　of　extreme　disaster　events　with　low　probability　and　high　risk　poses　a　serious　threat　to　the　safe　and　stable　operation　of　power　grids.　With　the　devel-opment　of　energy　internet　technology,　the　deep　integration　of　power　distribution,　natural　gas　and　transportation　networks　has　opened　a　promising　way　for　resilient　distribution　net-works.　This　paper　proposes　a　full-time　scale　resilience　enhancement　framework　for　an　in-tegrated　electricity-gas-transportation　coupled　system　oriented　to　energy　internet.　In　this　framework,　a　minimax　regret　robust　optimization　model　considering　the　uncertainty　of　ex-treme　disaster　attacks　is　developed　to　make　the　line　hardening　strategy　in　the　pre-disaster　stage,　which　is　solved　by　the　column-and-constraint　generation　algorithm.　Furthermore,　the　synthetic　restoration　model　considering　the　co-optimization　of　dynamic　dispatch　of　gas-fired　units,　network　reconfiguration　and　damaged　component　repair　is　established,　in　which　the　coupling　influence　of　the　gas　and　transportation　networks　on　the　restoration　strategy　during　the　disaster　and　post　disaster　stages　is　taken　into　account.　And　the　se-quential　cone　programming　method　and　generalized　Benders　decomposition　algorithm　is　implemented　to　solve　the　above　model.　Finally,　the　proposed　model　and　solution　method　are　validated　via　a　modified　33-bus　power　distribution　network　coupled　with　a　12-node　transportation　network　and　a　7-node　gas　network.　The　simulation　results　demonstrate　that　the　proposed　minmax　regret　robust　optimization　model　can　achieve　a　pre-disaster　defen-sive　strategy　with　less　conservativeness　in　contrast　to　the　conventional　robust　optimization　model.　Specifically,　the　cost　under　the　worst-case　attacks　by　the　former　has　reduced　by　11.52-22.29%　compared　to　the　latter.　Moreover,　the　influence　of　the　interdependent　criti-cal　infrastructure　networks　on　the　synthetic　restoration　strategy　in　the　disaster　and　post　-disaster　stages　has　been　investigated.　In　particular,　the　power　output　by　gas-fired　units　has　reduced　by　2699　kW　when　considering　the　operation　constraints　of　the　gas　network.　Additionally,　due　to　the　time-varying　characteristics　of　traffic　flow　and　commuting　time　in　the　transportation　network,　the　repair　time　for　the　damaged　components　is　shortened　by　1.09　h　while　the　preparation　time　of　crews　changes　from　2.5　to　1.5　h.(c)　2022　Elsevier　Inc.　All　rights　reserved.