We　study　a　robust　parameterized　submodular　function　maximization　inspired　by　[Mitrovic,　S,　I　Bogunovic,　A　Norouzi-Fardand　Jakub　Tarnawski　(2017).　Streaming　robust　submodular　maximization:　A　partitioned　thresholding　approach.　In　Proc.　NIPS,　pp.　4560-4569]　and　[Bogunovic,　I,　J　Zhao　and　V　Cevher　(2018).　Robust　maximization　of　nonsubmodular　objectives.　In　Proc.　AISTATS,　pp.　890-899].　In　our　setting,　given　a　parameterized　set　function,　there　are　two　additional　twists.　One　is　that　elements　arrive　in　a　streaming　style,　and　the　other　is　that　there　are　at　most　tau　items　deleted　from　the　algorithm＇s　memory　when　the　stream　is　finished.　The　goal　is　to　choose　a　robust　set　from　the　stream　such　that　the　robust　ratio　is　maximized.　We　propose　a　two-phase　algorithm　for　maximizing　a　normalized　monotone　robust　parameterized　submodular　function　with　a　cardinality　constraint　and　show　the　robust　ratio　is　close　to　a　constant　as　k　-＞　infinity.　In　the　end,　we　empirically　demonstrate　the　performance　of　our　algorithm　on　deletion　robust　support　selection　problem.