Radio　access　network　(RAN)　enables　large-scale　collection　of　sensitive　data.　Privacy-preserving　techniques　aim　to　learn　knowledge　from　sensitive　data　to　improve　services　without　compromising　privacy.　However,　as　the　data　scale　increases,　enforcing　privacy-preserving　techniques　on　sensitive　data　may　consume　a　considerable　amount　of　system　resources　and　impose　performance　penalties.　To　reduce　system　resource　consumption,　we　present　NetDP,　an　in-network　architecture　for　privacy-preserving　techniques　by　leveraging　programmable　switches　to　improve　resource　efficiency　(i.e.,　CPU　cycles,　network　bandwidth,　and　privacy　budgets).　The　key　idea　of　NetDP　is　to　accommodate　and　exploit　cryptographic　operators　to　reduce　resource　consumption　rather　than　repetitively　and　exhaustively　suppressing　the　impact　of　these　techniques.　To　the　best　of　our　knowledge,　this　is　the　first　time　that　privacy-preserving　techniques　in　a　large-scale　data　processing　system　have　been　enforced　on　programmable　switches.　Our　experiments　based　on　Tofino　switches　indicate　that　NetDP　significantly　reduces　computation　latency　(e.g.,　40.2%-55.8%　latency　in　computations)　without　impacting　fidelity.　IEEE