JPEG　reversible　data　hiding　(RDH)　refers　to　covert　communication　technology　to　accurately　extract　secret　data　while　also　perfectly　recovering　the　original　JPEG　image.　With　the　development　of　cloud　services,　a　large　number　of　private　JPEG　images　can　be　efficiently　managed　in　cloud　platforms　by　embedding　user　ID　or　authentication　labels.　Nevertheless,　data　embedding　operations　may　inadvertently　disrupt　the　encoding　sequence　of　the　original　JPEG　image,　resulting　in　severe　distortion　of　the　host　image　when　it　is　re-compressed　to　JPEG　format.　To　address　this　problem,　this　paper　proposes　a　new　JPEG　RDH　scheme　based　on　block　sorting　optimization　and　dynamic　iterative　histogram　modification.　We　firstly　design　a　block　ordering　optimization　strategy　by　combining　the　number　of　zero　coefficients　and　the　quantization　table　values　of　non-zero　coefficients　in　a　DCT　block.　Subsequently,　a　dynamic　iterative　histogram　modification　scheme　is　proposed　by　considering　the　local　features　and　embedding　capability　of　histograms　generated　from　different　texture　images.　According　to　the　given　payloads,　we　introduce　different　parameters　to　control　the　iterations　of　two-dimensional　histogram　and　then　adaptively　generate　the　optimal　histogram　modification　mapping,　which　can　realize　low　JPEG　file　size　increments　by　guaranteeing　most　of　the　AC　coefficients　unchanged　as　much　as　possible.　Numerous　experiments　have　shown　that　our　scheme　can　achieve　an　effective　balance　among　embedding　capacity,　visual　quality,　file　size　increment,　computational　complexity,　and　outperforms　the　state-of-the-arts　in　terms　of　the　above　metrics.