Since　its　introduction　in　2006,　Hadoop　technology　has　evolved　dramatically　and　the　Hadoop　ecosystem　has　flourished.　The　Hadoop　ecosystem　is　now　composed　of　more　than　60　components,　ranging　from　HDFS　and　MapReduce.　Hadoop＇s　architecture　makes　it　far　superior　to　other　products　in　large-scale　data　processing　and　analysis,　making　it　the　best　choice　for　all　industries.　This　makes　Hadoop　the　preferred　framework　for　data　analysis　and　processing　in　a　variety　of　industries.　With　the　widespread　application　of　Hadoop,　people　are　increasingly　concerned　about　the　data　trustworthiness　of　HDFS　such　as　the　explicit　storage　of　data　and　over-reliance　on　authentication　mechanisms.　In　order　to　ensure　the　trustworthiness　of　Hadoop　data　and　to　take　into　account　the　performance　factors　of　the　big　data　framework,　this　study　focuses　on　the　HDFS-based　data　trustworthiness　problem　and　the　use　of　node　classification,　data　encryption,　trustworthiness　measures　and　other　measures　to　comprehensively　enhance　the　trustworthiness　of　HDFS　file　system,　improve　the　existing　HDFS　system,　and　ensure　the　data　storage　communication　in　a　trustworthy　environment.　©　2021　IEEE.