In　this　paper,　the　robust　security　protection　control　for　switched　systems　is　studied.　A　robust　anti-disturbance　mechanism　using　the　Radial　Basis　Function　Neural　Network　(RBFNN)　is　proposed　for　switched　systems,　which　can　approximate　and　compensate　for　the　impact　of　unknown　disturbance　on　the　system　state.　Then,　a　network　security　protection　mechanism　based　on　encoder　and　decoder　is　presented,　which　has　the　ability　to　resist　the　dual　impact　on　the　feedback　information　caused　by　the　network　privacy　snooping　and　data　injection　attacks.　Accordingly,　stability　analysis　and　state-feedback　controller　design　are　given　for　the　switched　systems　under　unknown　disturbance,　network　privacy　snooping　and　injection　attacks.　Finally,　simulation　results　illustrate　the　effectiveness　of　the　proposed　method.　©　2024　Elsevier　Inc.