To　solve　the　problem　of　low　detection　rate　and　long　detection　time　of　the　existing　DoS　attack　detection　algorithm,　a　DoS　attack　detection　algorithm　was　proposed　based　on　higher-order　statistics.　The　network　traffic　data　packets　were　segmented　and　quantified　in　the　algorithm.　Followed,　the　characteristics　of　the　accumulation　was　extracted　which　was　applied　to　the　detection　of　DoS　attacks.　By　analyzing　the　1998　DARPA　intrusion　detection　data　set,　the　algorithm　can　effectively　detect　DoS　attacks.　Compared　with　the　traditional　anomaly　detection　method　entropy　based　on　network　traffic,　the　detection　accuracy　is　greatly　improved.　In　the　time　window　of　1　s,　the　detection　rate　increases　by　8%.　©　2017,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.