In　past　years,　various　encrypted　algorithms　have　been　proposed　to　fully　or　partially　protect　the　multimedia　content　in　view　of　practical　applications.　In　the　context　of　digital　TV　broadcasting,　transparent　encryption　only　protects　partial　content　and　fulfills　both　security　and　quality　requirements.　To　date,　only　a　few　reference-based　works　have　been　reported　to　evaluate　the　quality　of　transparently　encrypted　images.　However,　these　works　are　incapable　of　reference-unavailable　conditions.　In　this　paper,　we　conduct　the　first　attempt　that　proposes　a　novel　quality　evaluator　in　the　absence　of　reference　images.　The　key　strategy　of　the　proposed　metric　lies　in　extracting　features　by　considering　the　motivation　of　transparently　encrypted　images.　Specifically,　given　that　encrypted　images　prevent　content　from　being　easily　recognized,　several　features,　including　correlation　coefficient,　information　entropy,　and　intensity　statistic,　are　preliminarily　extracted　to　estimate　visual　recognizability.　Meanwhile,　considering　that　encrypted　images　are　avoided　since　they　are　of　extremely　low　quality,　we　also　capture　many　features　to　measure　the　distortions　on　multiple　quality-sensitive　image　attributes,　such　as　naturalness,　structure,　and　texture.　Finally,　the　quality　evaluator　is　built　by　bridging　all　extracted　features　and　corresponding　quality　scores　via　a　regression　module.　Experimental　results　demonstrate　that　the　proposed　method　is　superior　to　the　mainstream　no-reference　quality　evaluation　methods　designed　for　synthetically　distorted　images　and　possesses　a　close　approximation　to　state-of-the-art　reference-based　methods　designed　for　encrypted　images.