@article{2751,
  keywords = {Characteristic indices, Communications networks, Cryptography, Data communication systems, Intangible cultural heritages, Learning algorithms, machine learning, Machine learning algorithms, Machine-learning, Network-based, On-machines, Sensitive informations, Specific values, Target tracking, Targets tracking, Telecommunication networks},
  author = {X. Zhang and Y. Jin},
  title = {A Method of Protecting Sensitive Information in Intangible Cultural Heritage Communication Network Based on Machine Learning},
  abstract = {In 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.},
  year = {2023},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  volume = {13656 LNCS},
  pages = {214-227},
  issn = {03029743},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148691741&doi=10.1007%2f978-3-031-20099-1_18&partnerID=40&md5=e2181976dbe5f6bbe46b5f83b97a2af3},
  doi = {10.1007/978-3-031-20099-1_18},
  language = {English},
}