The　characteristics　of　volume,　variety,　velocity　and　value　for　big　data　have　made　present　privacy　protection　methods　less　effective　in　the　protection　of　user　privacy　to　meet　the　emerging　requirements.　In　this　paper,　we　analyze　the　spatial　and　temporal　effects　the　access　to　the　data　on　privacy　disclosure　and　propose　an　access　control　model　to　protect　user　privacy　that　is　related　to　the　number　and　the　frequency　of　access　in　the　access　history　of　the　requester.　By　introducing　the　notions　of　the　privacy　threshold,　the　requested　items　and　the　access　history,　the　proposed　access　control　model　can　make　the　decision　on　whether　to　allow　the　current　access　request　to　the　protected　privacy　information.　This　method　can　cope　with　the　dynamic　and　correlative　nature　of　the　data　for　privacy　protection　while　reducing　the　cost　of　computation.