Recoverable Identifier

arXiv:2604.20771 · detector doi_compliance · incontrovertible · 2026-05-20 01:36:57.250042+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1109/TITS.2023.3271300.Yanmin) was visible in the surrounding text but could not be confirmed against doi.org as printed.

Paper page Integrity report arXiv Try DOI

Evidence text

http://dx.doi.org/10. 3390/electronics11223658. Yang, L., Moubayed, A., & Shami, A. (2021). MTH-ids: A multitiered hybrid intrusion detection system for internet of vehicles. IEEE Internet of Things Journal, 9(1), 616–632. Yang, T., Murguia, C., & Lv, C. (2023). Risk assessment for connected vehicles under stealthy attacks on vehicle-to-vehicle networks. IEEE Transactions on Intelli- gent Transportation Systems, 24(12), 13627–13638. http://dx.doi.org/10.1109/TITS. 2023.3271300. Yanmin, C., Sarkar, A., Zain, J. M., Bhar, A., Noorwali, A., & Othman, K. M. (2025). Leveraging LSTM and GRU-based deep neural coordination in intelligent transportation to strengthen security in the internet of vehicles. International Journal of Machine Learning and Cybernetics, 16(4), 2431–2467. Yazdinejad, A., Kazemi, M., Parizi, R. M., Dehghantanha, A., & Karimipour, H. (2023). An ensemble deep learning model for cyber threat hunting in industrial internet of things. Digital Communications and Networks, 9(1), 101–110. http://dx.doi.org/10. 1016/j.dcan.2021.12.009. Machine Learning with Applications 23 (2026) 100859 15

Evidence payload

{
  "printed_excerpt": "http://dx.doi.org/10. 3390/electronics11223658. Yang, L., Moubayed, A., & Shami, A. (2021). MTH-ids: A multitiered hybrid intrusion detection system for internet of vehicles. IEEE Internet of Things Journal, 9(1), 616\u2013632. Yang, T., Murguia",
  "reconstructed_doi": "10.1109/TITS.2023.3271300.Yanmin",
  "ref_index": 8,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}