{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T07:45:33Z","timestamp":1763451933324,"version":"3.45.0"},"reference-count":29,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Security and Privacy"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In order to address the data privacy issues in real\u2010time collaboration in P2P virtual scenes, this paper proposes a privacy protection transmission framework based on the Brakerski Fan Vercauteren homomorphic encryption scheme. The proposed framework allows for direct computation of ciphertext, ensuring end\u2010to\u2010end privacy protection while maintaining acceptable real\u2010time performance. We have built a high\u2010performance experimental platform consisting of an Intel Xeon Gold edge server with 128\u2009GB of memory, an NVIDIA RTX A6000 GPU, and a Docker based Ubuntu environment that integrates TensorFlow and PyTorch for encryption performance testing and behavioral modeling. The experimental results show that homomorphic encryption supports addition and multiplication operations in ciphertext form, effectively preventing sensitive information leakage. Compared with AES, the BFV based scheme shows higher average latency, but reduces privacy leakage by over 93%. In four real\u2010world collaboration scenarios, the leakage rate decreased from 86.25% to 5.5%. When the number of nodes increased from 10 to 200, the system throughput decreased from 43.2 to 28.4\u2009MB\/s, while the CPU utilization increased from 68% to 87%, indicating a reasonable trade\u2010off between computation and security. In addition, the integrated edge offloading mechanism reduces encryption latency from 180 to 95\u2009ms, an increase of 36%, while maintaining complete ciphertext confidentiality during processing. These findings validate that the proposed BFV based P2P collaboration framework achieves advanced privacy protection and real\u2010time scalability, providing a feasible and secure solution for remote design, distributed virtual training, and other privacy sensitive applications. Future research will focus on optimizing lightweight encryption and adaptive scheduling mechanisms for wider deployment in heterogeneous P2P environments.<\/jats:p>","DOI":"10.1002\/spy2.70137","type":"journal-article","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T01:55:16Z","timestamp":1762998916000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Privacy\u2010Preserving Framework for Real\u2010Time\n                    <scp>P2P<\/scp>\n                    Virtual Scene Transmission Using Homomorphic Encryption and Edge Offloading"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7185-2341","authenticated-orcid":false,"given":"Wangqin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mathematics and Information Science Nanchang Normal University  Nanchang 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