Cloud　computing　is　witnessing　a　fast　development　and　widespread　adoption　due　to　its　cost-effective　and　resource　efficient　services.　Nevertheless,　security　risks　are　not　outsourced　and　remain　under　both　cloud　service　providers　and　consumers　responsibility.　One　of　the　main　challenges　is　how　to　evaluate　the　security　level　of　cloud　services.　Current　methods　are　mostly　focused　on　solving　the　problem　of　cloud　services　evaluation　from　a　single　user　perspective.　However,　cloud　computing　is　a　multi-　tenant　environment　that　serves　a　large　number　of　tenants　with　multiple　end-users　at　the　same　time.　This　heterogeneity　leads　to　different,　and　often,　conflicting　security　requirements.　In　this　paper,　we　propose　a　multi-tenant　cloud　services　evaluation　framework,　whereby　service　selection　is　carried　out　per　groups　of　tenants　rather　than　per　a　single　user.　To　ensure　that　all　tenants＇　requirements　are　satisfied,　we　first　consider　the　similarity　between　cloud　service　providers　performances　and　tenants＇　requirements.　Tenants＇　weights　are　determined　in　an　objective　way　based　on　their　risk　attitudes　and　contributions　to　the　overall　group　decision　using　fuzzy　TOPSIS　technique.　The　final　ranking　of　the　alternatives　is　further　guided　by　consensus　analysis　process　to　guarantee　a　final　solution　with　the　highest　level　of　agreement.