BANK TIZIMIDA TARMOQ HUJUMLARIDAN HIMOYALASH USUL VA ALGORITMLARI
Ключевые слова:
Tarmoq turlari, tarmoq hujumlar, himoyalash algoritmlariАннотация
Ushbu maqolada bank tizimdagi tarmoq turlari va ularga bo‘ladigan tarmoq hujumlari ko‘rib chiqilgan bo‘lib, shuningdek, bank to‘lov tizimida tarmoq hujumlarini aniqlash usullari va ularni tahlili keltirilgan.
Библиографические ссылки
O‘zbekiston Respublikasining “Avtomatlashtirilgan bank tizimida axborotni muhofaza qilish to‘g‘risida”gi va “O‘zbekiston Respublikasining Markaziy banki to‘g‘risida”gi qonunlari hamda O‘zbekiston Respublikasi Prezidentining 2018-yil 8-avgustdagi PF-5505-son “Norma ijodkorligi faoliyatini takomillashtirish konsepsiyasini tasdiqlash to‘g‘risida”gi Farmoniga muvofiq O‘zbekiston Respublikasi Markaziy banki Boshqaruvi qaror.
O‘zbekiston Respublikasining qonuni “Banklar va bank faoliyati to‘g‘risida”gi O‘zbekiston Respublikasi qonuniga o‘zgartirish va qo‘shimchalar kiritish haqida Qonunchilik palatasi tomonidan 2019-yil 22-iyulda qabul qilingan Senat tomonidan 2019-yil 11-oktabrda ma’qullangan qarori.
Bozorov, Suhrobjon. "DDoS Attack Detection via IDS: Open Challenges and Problems." 2021 International Conference on Information Science and Communications Technologies (ICISCT). IEEE, 2021.
Xoliyarov, Farhod, Sherzod Gulomov, and Suhrobjon Bozorov. "The Impact of Artificial Neural Network Architecture on Network Attack Detection." Proceedings of the 7th International Conference on Future Networks and Distributed Systems. 2023.
Xie, Y., Tang, S., Huang, X., Tang, C., & Liu, X. (2013). Detecting latent attack behavior from aggregated Web traffic. Computer Communications, 36(8), 895-907.
Gyamfi, N. K., & Abdulai, J. D. (2018, November). Bank fraud detection using support vector machine. In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp. 37-41). IEEE.
Bhuyan M. H., Bhattacharyya D. K., Kalita J. K. Network anomaly detection: methods, systems and tools //Ieee communications surveys & tutorials. – 2013. – Т. 16. – №. 1. – С. 303-336.
Wattanapongsakorn, N., Srakaew, S., Wonghirunsombat, E., Sribavonmongkol, C., Junhom, T., Jongsubsook, P., & Charnsripinyo, C. (2012, June). A practical network-based intrusion detection and prevention system. In 2012 IEEE 11th international conference on trust, security and privacy in computing and communications (pp. 209-214). IEEE.
https://www.flowmon.com/en/solutions/security-operations/network-behavior-analysis-anomaly-detection
https://www.zabbix.com/network_monitoring
