This　work　presents　a　retrieval　scheme　for　encrypted　JPEG　images　based　on　Markov　process.　In　our　scheme,　the　stream　cipher　and　permutation　encryption　are　combined　to　encrypt　JPEG　images,　which　are　then　uploaded　to　a　database　server.　After　that,　the　server　without　knowing　the　original　content　can　extract　features　from　the　transition　probability　matrices　of　the　AC　coefficients　of　encrypted　query　image,　in　which　those　coefficients　are　modeled　by　Markov　process.　With　the　multi-class　support　vector　machine　(SVM),　the　features　of　encrypted　query　image　can　be　converted　into　a　vector　with　low　dimensionality　determined　by　the　number　of　image　categories.　The　encrypted　database　images　are　conducted　similarly.　After　low-dimensional　vector　representation,　the　similarity　between　encrypted　query　image　and　database　image　may　be　measured　by　calculating　the　distance　of　their　corresponding　vectors.　At　the　client　side,　the　encrypted　images　returned　by　the　server　are　decrypted　to　the　plaintext　images　using　encryption　key.　The　proposed　scheme　can　preserve　file　compliance　and　file　size　for　encrypted　JPEG　images,　while　providing　privacy-preserving　image　retrieval.