When　a　swarm　composed　of　multiple　robots　or　drones　detects　an　unknown　external　node　during　the　execution　of　a　task,　it　needs　to　identify　its　intention　to　decide　how　to　respond.　However,　the　internal　nodes　of　the　swarm　will　be　attacked　against　the　measurement　signal,　resulting　in　increased　measurement　error,　and　then　the　intention　identification　of　the　external　nodes　will　fail,　posing　a　threat　to　the　swarm.　To　solve　this　problem,　a　distributed　control　algorithm　for　swarm　which　considers　the　network　attack　is　designed.　In　this　algorithm,　the　control　law　is　the　flocking　algorithm.　When　an　unknown　external　node　is　detected,　firstly,　the　internal　node　determines　whether　it　is　under　network　attack　based　on　the　designed　attack　recognition　algorithm.　Then,　according　to　the　distributed　Kalman　filtering　based　on　attack　identification　strategy,　the　state　of　external　nodes　is　estimated　to　minimize　the　impact　of　network　attacks.　Next,　the　similarity　between　the　expected　trajectory　and　the　measured　trajectory　is　calculated　according　to　the　Fréchet　distance,　and　the　distributed　consensus　algorithm　is　used　to　judge　the　intention　of　the　external　node,　control　swarm　escape　or　converge.　Finally,　the　effectiveness　of　the　proposed　method　is　demonstrated　by　simulation　results.　©　2024　Northeast　University.　All　rights　reserved.