In　network　security　situation　awareness　system,　the　data　are　characterized　by　huge　quantities,　numerous　features,　redundancy,　etc.　These　features　may　seriously　impact　the　efficiency　of　situation　evaluation　and　prediction.　This　paper　proposes　a　principal　component　analysis　algorithm　based　on　projection　pursuit　(PP-PCA)　to　solve　these　problems.　Combined　with　particle　swarm　optimization　and　exterior　point　penalty　function,　PP-PCA　projects　the　data　onto　one-dimensional　plane　then　figures　out　several　composite　indicators　which　play　leading　roles.　The　simulate　experiment　shows　that　it　can　overcome　the　redundancy　and　improve　the　efficiency　of　the　situation　evaluation　and　prediction.　©　Springer-Verlag　Berlin　Heidelberg　2012.