Green　edge　computing　aims　to　reasonably　allocate　computing　resources　on　the　premise　of　ensuring　the　reliability　of　information　services.　The　computing　power　gap　between　terminal　and　edge　server　makes　the　traditional　encryption　algorithm　waste　too　much　energy　when　dealing　with　massive　redundant　data.　How　to　improve　encryption　efficiency　and　reduce　the　computing　consumption　of　massive　data　terminal　equipment　on　the　premise　of　ensuring　data　security　is　one　of　the　goals　of　green　edge　computing.　We　proposed　a　data　compression　and　encryption　scheme　based　on　compression　sensing,　which　greatly　reduces　the　computing　consumption　of　computing　limited　data　terminals;　At　the　same　time,　the　hyper　chaotic　system　is　used　to　further　encrypt　the　data　by　Arnold　transform,　bitwise　XOR　and　data　random　scrambling.　In　order　to　solve　the　problem　that　compressed　sensing　can　not　accurately　recover　data,　we　designed　a　nonlinear　encryption　scheme　based　on　Chinese　Remainder　Theorem　as　a　supplement.　The　simulation　results　show　that　the　proposed　data　compression　and　encryption　method　is　effective　and　reliable,　which　has　high　security　performance,　compression　ability　for　text　data　and　images,　and　high　recovery　ability　when　the　compression　ratio　is　more　than　0.5.