Data　encryption　is　a　practical　approach　to　protect　biomedical　image　information　security.　Towards　the　massive　amount　of　data　generated　in　the　medical　field,　chaotic　model　cryptosystems,　with　high　sensitivity　to　initial　conditions　and　overall　stability　and　randomness　of　the　system,　are　inevitably　becoming　an　appropriate　platform　for　communication　protection.　This　paper　proposes　a　privacy-preserving　Hybrid　encryption　scheme　based　on　Chaos　theory　and　ECC　Algorithm　(HCEA)　for　the　secure　delivery　of　medical　data.　Specifically,　we　employ　the　logistic　map　with　randomness　characteristics　to　protect　published　data　privacy　against　the　complex　network　environment　and　other　non-subscribers.　The　proposed　cryptosystem　can　essentially　achieve　the　secrecy　effect　of　a　＂one-time　pad.＂　To　achieve　double　encryption　of　textual　information　and　keys,　we　propose　an　improved　image　steganography　technique　with　secondary　scrambling　encryption　of　carrier　images　by　the　MLNCML　system,　enhancing　encryption　efficiency　and　security.　Different　from　existing　standard　LSB　image　encryption　methods,　the　HCEA　can　encrypt　initial　parameters　of　logistic　and　MLNCML　with　the　asymmetric　encryption　ECC　algorithm　while　guaranteeing　the　security　of　key　distribution　in　complex　network　environments.　The　security　proof　and　performance　evaluation　show　that　the　proposed　HCEA　scheme　is　secure　in　medical　data　transmission　and　effective　in　practice.