Task　matching　in　crowdsourcing　has　been　extensively　explored　with　the　increasing　popularity　of　crowdsourcing.　However,　privacy　of　tasks　and　workers　is　usually　ignored　in　most　of　exiting　solutions.　In　this　paper,　we　study　the　problem　of　privacy-preserving　task　matching　for　crowdsourcing　with　multiple　requesters　and　multiple　workers.　Instead　of　utilizing　proxy　re-encryption,　we　propose　a　proxy-free　task　matching　scheme　for　multi-requester/multi-worker　crowdsourcing,　which　achieves　task-worker　matching　over　encrypted　data　with　scalability　and　non-interaction.　We　further　design　two　different　mechanisms　for　worker　revocation　including　Server-Local　Revocation　(SLR)　and　Global　Revocation　(GR),　which　realize　efficient　worker　revocation　with　minimal　overhead　on　the　whole　system.　The　proposed　scheme　is　provably　secure　in　the　random　oracle　model　under　the　Decisional　qq-Combined　Bilinear　Diffie-Hellman　(qq-DCDBH)　assumption.　Comprehensive　theoretical　analysis　and　detailed　simulation　results　show　that　the　proposed　scheme　outperforms　the　state-of-the-art　work.　©　2020　IEEE.