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Intrusion detection methods can detect local area network attacks before causing widespread damage, and develop corresponding defense measures accordingly. To ensure the operational security of the local area network, a local area network intrusion localization and detection method based on the GBDT optimization algorithm is proposed. Consider the composition structure and working principle of the local area network, and construct a mathematical model of the local area network. Under this model, intrusion detection standards are set based on the attack principles of different intrusion types. Real time operation data collection and preprocessing of the local area network, extracting the operational characteristics of the local area network from both time-domain and frequency-domain aspects. Using the GBDT optimization algorithm to construct a local area network intrusion classifier, matching the characteristics of local area network operation data, tracking the location of local area network intrusion sources, and ultimately obtaining the detection results of intrusion source localization, intrusion status, and type. Through performance testing experiments, it was found that compared with traditional methods, the optimized design method reduced the intrusion localization error by 5.75m, and improved the correct detection rates of intrusion types and intrusion quantities by 13.8% and 15.4%, respectively. This indicates that the optimized design method has significant advantages in localization and detection performance.