The　past　years　have　witnessed　increasingly　widespread　terrorism,　violently　destroying　world　peace　and　regional　prosperity.　Therefore,　uncovering　terrorist　plots　has　become　the　most　crucial　step　for　eliminating　terrorist　attacks.　However,　with　the　terrorist　scheme　being　disguised　under　the　huge　amount　of　data　flow　on　the　internet,　identifying　terrorist　organizations　still　remains　challenging.　Since　many　terrorist　organizations　are　prone　to　launch　terrorist　attacks　together,　here,　we　model　their　relationships　as　a　Terrorist　Organization　Alliance　(TOA)　network　and　propose　a　novel　method　to　identify　the　key　terrorist　organizations　in　the　TOA　network.　The　TOA　network　utilizes　existing　key　nodes　in　order　to　extract　useful　information,　and,　with　the　help　of　the　entropy　weight　method,　the　new　solution　to　the　TOA　network　is　effective　and　precise.　The　experiments　are　performed　on　the　dataset　from　the　Global　Terrorism　Database,　and　the　results　are　statistically　validated　through　t-tests　and　convergence　analysis.　Compared　with　the　traditional　methods,　our　method　is　proven　to　be　superior　in　terms　of　measure　the　harm　of　terrorist　attack　organizations　and　find　the　key　terrorist　organizations.