In　recent　years,　immunization　strategies　have　been　developed　for　stopping　epidemics　in　complex-network-like　environments.　Yet　it　still　remains　a　challenge　for　existing　strategies　to　deal　with　dynamically-evolving　networks　that　contain　community　structures,　though　they　are　ubiquitous　in　the　real　world.　In　this　paper,　we　examine　the　performances　of　an　autonomy-oriented　distributed　search　strategy　for　tackling　such　networks.　The　strategy　is　based　on　the　ideas　of　self-organization　and　positive　feedback　from　Autonomy-Oriented　Computing　(AOC).　Our　experimental　results　have　shown　that　autonomous　entities　in　this　strategy　can　collectively　find　and　immunize　most　highly　connected　nodes　in　a　dynamic,　community-　based　network　within　a　few　steps.