Networked　control　systems　(NCSs)　suffer　from　various　communication　imperfections,　including　varying　transmission　intervals,　packet　losses,　and　FDI　attacks.　The　majority　of　the　existing　literature　on　NCSs　tends　to　emphasize　certain　aspects　while　neglecting　others.　In　this　paper,　we　propose　a　general　framework　for　addressing　the　stabilization　problem　of　networked　nonlinear　systems　that　incorporates　multiple　stochastic　transmission　intervals　(MSTIs),　successive　packet　losses　(SPLs),　and　false　data　injection　(FDI)　attacks.　We　assume　that　the　nonlinear　system　can　be　precisely　modeled　using　a　Takagi-Sugeno　fuzzy　system.　MSTIs　can　be　described　using　the　Categorical　distribution,　while　both　the　sensor-to-controller　channel　and　the　controller-to-actuator　channel　are　affected　by　SPLs　and　FDI　attacks.　In　order　to　facilitate　the　stabilization　problem,　we　first　establish　the　equivalent　stochastic　transmission　interval　between　adjacent　non-packet-loss　instants,　where　the　occurrence　probability　of　the　length　of　the　equivalent　transmission　interval　can　be　accurately　calculated　by　using　the　probabilistic　information　of　SPLs　and　MSTIs.　Furthermore,　considering　two-channel　FDI　attacks,　a　discrete-time　T-S　fuzzy　system　model　is　obtained.　The　controller　design　conditions,　represented　by　linear　matrix　inequalities　(LMIs),　are　derived　based　on　this　model.　Specifically,　using　a　novel　matrix　reconstruction　approach,　the　dimension　of　the　obtained　controller　design　condition　does　not　change　with　the　number　of　maximum　packet　losses　and　the　number　of　MSTIs,　which　is　more　general　than　existing　results　and　avoids　the　high　computational　complexity　associated　with　solving　LMIs　in　some　cases.　Finally,　the　effectiveness　of　the　proposed　method　is　demonstrated　through　a　numerical　example.　　©　1993-2012　IEEE.