AXBOROT KOMMUNIKATSIYA TARMOQLARIDA KIBERHUJUMLARNI ANIQLASH USUL VA VOSITALARI
Keywords:
Kibertahdidlar, Ransomware, Phishing, DDoS hujumlari, SQL ineksiya, Tarmoq xavfsizligi, NGFW, SIEM, XDR, ZTNA, Deception Technology, Honeypot, Proaktiv himoya choralari, Kiberjinoyatlar statistikasiAbstract
Maqolada zamonaviy kibertahdidlarning ortib borayotgan xavfi, ularning turlari (ransomware, phishing, DDoS, SQL ineksiya va boshqalar) va 2025-yilgi global statistik maʼlumotlar tahlil qilingan. Kiberhujumlarning asosiy maqsadlari (pul, moliyaviy maʼlumotlar, shaxsiy identifikatsiya maʼlumotlari) va ularning ishlab chiqarish, taʼlim va tibbiyot kabi sektorlarga taʼsiri koʻrib chiqilgan. Tarmoq xavfsizligini taʼminlashda NGFW, SIEM, XDR, ZTNA kabi zamonaviy himoya texnologiyalarining imkoniyatlari va ularning anʼanaviy usullardan farqlari jadval shaklida taqqoslangan. Deception Technology (honeypotlar) orqali hujumchilarni aldash va ularning taktikalarini oʻrganish metodlari bayon etilgan. Maqolada foydalanuvchilarni xavfsizlik boʻyicha oʻqitish, koʻp faktorli autentifikatsiya va tizimli yangilanishlarni oʻtkazishning ahamiyati taʼkidlangan. Tadqiqot kibertahdidlarga qarshi kompleks yondashuv va proaktiv choralarni joriy etish zarurligini koʻrsatadi.
References
1. N. Hoque, M.H. Bhuyan, R.C. Baishya, D.K. Bhattacharyya, J.K. Kalita, Network attacks: Taxonomy, tools and systems, 2014, Journal of Network and Computer Applications, p.307-324, doi: 10.1016/j.jnca.2013.08.001 ;
2. S Bozorov, N Akhmedova, D Qurbonaliyeva, K Gultekin, Survey on honeypot: Detection, countermeasures and future with MI. AIP Conference Proceedings, 2024. doi: 10.1063/5.0242098 ;
3. https://www.stationx.net/?s=cyber-security-breach-statistics%252025
4. Z. Alkhalil; Ch. Hewage; L. Nawaf; I. Khan, Phishing Attacks: A Recent Comprehensive Study and a New Anatomy, in 2021 Editor's Pick: Computer Science, doi:10.3389/fcomp.2021.563060 ;
5. Meland PH, Bayoumy YFF, Sindre G. The ransomware-as-a-service economy within the darknet. Comput Secur. 2020; 92:101762. doi:10.1016/j.cose.2020.101762 ;
6. Y. Al-Dunainawi, B. R. Al-Kaseem and H. S. Al-Raweshidy, "Optimized artificial intelligence model for DDoS detection in SDN environment", IEEE Access, vol. 11, pp. 106733-106748, 2023.
7. J. Jiang, G. Han, F. Wang, L. Shu, M. Guizani, An efficient distributed trust model for wireless sensor networks, IEEE Trans. Parallel Distrib. Syst., 26 (5) (2014), pp. 1228-1237,
8. R.P. van Heerden, B. Irwin, I.D. Burke va L. Leenen, Description of a Network Attack Ontology Presented Formally, 2021, Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities, p 343–368, doi: 10.1007/978-3-030-72236-4_14 ;
9. M. Raunds, N. Pentgraft, Diversity in Network Attacker Motivation: A Literature Review, 2009, International Conference on Computational Science and Engineering, doi: 10.1109/CSE.2009.178.;
10. M. Agarwal, K. S. Gill, R. Chauhan, A. Kapruwan, D. Banerjee, 2024, 3rd International Conference for Innovation in Technology (INOCON), doi: 10.1109/INOCON60754.2024.10512250 ;
11. R. Ding, L. Sun, W. Zang, L. Dai, Z. Ding, B. Xu, Towards universal and transferable adversarial attacks against network traffic classification, 2024, Journal of Computer Networks, doi: 10.1016/j.comnet.2024.110790 ;
12. B. Dorsemaine, J.P. Gaulier, J.P Wary, N. Kheir, P. Urien, Internet of Things: A Definition and Taxonomy, In Proceedings of the 2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies, Cambridge, UK, 9–11 September 2015. doi: 10.1109/NGMAST.2015.71 ;
13. Z. Doffman, Cyberattacks On IOT Devices Surge 300%, 2019, Measured in Billions.