02482nas a2200349 4500000000100000000000100001008004100002653002700043653002800070653001700098653003100115653003400146653002400180653002100204653003200225653002100257653001800278653001600296653002700312653002000339653002000359653002100379653003100400100001300431700001100444245012900455856015300584300001200737490001500749520135500764022001302119 2023 d10aCharacteristic indices10aCommunications networks10aCryptography10aData communication systems10aIntangible cultural heritages10aLearning algorithms10amachine learning10aMachine learning algorithms10aMachine-learning10aNetwork-based10aOn-machines10aSensitive informations10aSpecific values10aTarget tracking10aTargets tracking10aTelecommunication networks1 aX. Zhang1 aY. Jin00aA Method of Protecting Sensitive Information in Intangible Cultural Heritage Communication Network Based on Machine Learning uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85148691741&doi=10.1007%2f978-3-031-20099-1_18&partnerID=40&md5=e2181976dbe5f6bbe46b5f83b97a2af3 a214-2270 v13656 LNCS3 aIn order to accurately identify the sensitive information in the intangible cultural heritage communication network and realize the reasonable protection of intangible cultural heritage data, a method for protecting the sensitive information in the intangible cultural heritage communication network based on machine learning is proposed. With the support of machine learning algorithm, the distance measurement results are solved, and then the specific values of compressed characteristic indexes are calculated by establishing a random measurement matrix to complete the tracking and processing of the target parameters of intangible cultural heritage. On this basis, according to the encryption processing results of sensitive information, the implementation standard of OSBE protocol is established, and then with the help of the formed sensitive information processing process, the effective protection of sensitive information of intangible cultural heritage communication network is realized. The results of comparative experiments show that under the effect of machine learning algorithm, the recognition accuracy of the network host for the sensitive information of intangible cultural heritage has significantly improved, and it really has strong practical value in the reasonable protection of intangible cultural heritage data parameters. a03029743