Aplikasi Honeypot dalam Keamanan Jaringan untuk Mendeteksi Serangan Siber pada Infrastruktur TI
DOI:
https://doi.org/10.32664/j-intech.v13i01.1924Kata Kunci:
Analisis Log AI, Deteksi Serangan Siber, Honeypot, Pemantauan Intrusi, Keamanan JaringanAbstrak
Risiko keamanan yang tinggi yang rentan terhadap peretasan dan eksploitasi oleh aktor jahat untuk mencuri data atau informasi seringkali muncul akibat kurangnya kesadaran mengenai pentingnya penerapan sistem keamanan jaringan yang kuat. Kelalaian ini menciptakan celah yang dapat dengan mudah dimanfaatkan oleh penyerang untuk memulai pelanggaran. Salah satu pendekatan yang menonjol dalam keamanan jaringan adalah penggunaan Honeypot, yang merujuk pada metode yang dirancang untuk membuat server tipu yang meniru server asli. Honeypot sengaja dirancang untuk menarik perhatian peretas siber dan memfasilitasi akses mereka ke server jebakan, sehingga memungkinkan pemantauan dan analisis aktivitas mereka tanpa mengorbankan integritas server utama. Untuk mencapai keamanan jaringan yang optimal, pengujian Honeypot yang komprehensif sangat penting. Proses pengujian ini berfungsi sebagai metrik dasar dalam mengevaluasi efektivitas dan kinerja sistem Honeypot dalam mengurangi ancaman siber.
Referensi
J. Williams, M. Edwards, and J. Gardiner, “Time-to-Lie: Identifying Industrial Control System Honeypots Using the Internet Control Message Protocol,†2024. [Online]. Available: https://arxiv.org/abs/2410.17731
A. Albaseer, N. Abdi, M. Abdallah, M. Qaraqe, and S. Alkuwari, “FedPot: A Quality-Aware Collaborative and Incentivized Honeypot-Based Detector for Smart Grid Networks,†2024. [Online]. Available: https://arxiv.org/abs/2407.02845
N. Kaur and L. Gupta, “Explainable AI for Securing Healthcare in IoT-Integrated 6G Wireless Networks,†2025. [Online]. Available: https://arxiv.org/abs/2505.14659
P. B. Lopez, P. Nespoli, and M. G. Perez, “Cyber Deception Reactive: TCP Stealth Redirection to On-Demand Honeypots,†2024. [Online]. Available: https://arxiv.org/abs/2402.09191
M. Kahlhofer and S. Rass, “Application Layer Cyber Deception Without Developer Interaction,†in 2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), IEEE, Jul. 2024, pp. 416–429. doi: 10.1109/EuroSPW61312.2024.00053.
Y. L. Aung et al., “HoneyWin: High-Interaction Windows Honeypot in Enterprise Environment,†2025. [Online]. Available: https://arxiv.org/abs/2505.00465
U. Ubaidillah, T. Taryo, and A. Hindasyah, “Analisis dan Implementasi Honeypot Honeyd Sebagai Low Interaction Terhadap Serangan Distributed Denial Of Service (DDOS) dan Malware,†JTIM : Jurnal Teknologi Informasi dan Multimedia, vol. 5, no. 3, pp. 208–217, Oct. 2023, doi: 10.35746/jtim.v5i3.405.
Y. Wang, Z. Su, A. Benslimane, Q. Xu, M. Dai, and R. Li, “Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach,†2023. [Online]. Available: https://arxiv.org/abs/2211.01772
A. Said, “On explaining recommendations with Large Language Models: a review,†Front Big Data, vol. 7, Jan. 2025, doi: 10.3389/fdata.2024.1505284.
Y. Wang, T. Gu, Y. Teng, Y. Wang, and X. Ma, “HoneypotNet: Backdoor Attacks Against Model Extraction,†2025. [Online]. Available: https://arxiv.org/abs/2501.01090
M. Nawrocki, J. Kristoff, R. Hiesgen, C. Kanich, T. C. Schmidt, and M. Wählisch, “SoK: A Data-driven View on Methods to Detect Reflective Amplification DDoS Attacks Using Honeypots,†in 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), IEEE, Jul. 2023, pp. 576–591. doi: 10.1109/EuroSP57164.2023.00041.
J. Landsborough, N. C. Rowe, T. D. Nguyen, and S. Fugate, “WiP: Deception-in-Depth Using Multiple Layers of Deception,†2024. [Online]. Available: https://arxiv.org/abs/2412.16430
A. Javadpour, F. Ja’fari, T. Taleb, M. Shojafar, and C. Benzaïd, “A comprehensive survey on cyber deception techniques to improve honeypot performance,†Comput Secur, vol. 140, p. 103792, May 2024, doi: 10.1016/j.cose.2024.103792.
K. Highnam, Z. Hanif, E. Van Vogt, S. Parbhoo, S. Maffeis, and N. R. Jennings, “Adaptive Experimental Design for Intrusion Data Collection,†2023. [Online]. Available: https://arxiv.org/abs/2310.13224
L. Sousa, J. CecÃlio, P. Ferreira, and A. Oliveira, “Reconfigurable and Scalable Honeynet for Cyber-Physical Systems,†2024. [Online]. Available: https://arxiv.org/abs/2404.04385
Y. Otoum, A. Asad, and A. Nayak, “Blockchain Meets Adaptive Honeypots: A Trust-Aware Approach to Next-Gen IoT Security,†2025. [Online]. Available: https://arxiv.org/abs/2504.16226
Z. Peng, Y. He, J. Ni, and B. Niu, “Bypassing DARCY Defense: Indistinguishable Universal Adversarial Triggers,†2024. [Online]. Available: https://arxiv.org/abs/2409.03183
H. Q. Ngo, M. Guo, and H. Nguyen, “Catch Me if You Can: Effective Honeypot Placement in Dynamic AD Attack Graphs,†2023. [Online]. Available: https://arxiv.org/abs/2312.16820
Irfan Murti Raazi, Ima Dwitawati, and Putri Nabila, “Uji Vulnerability Assessment Dalam Mengetahui Tingkat Keamanan Web Aplikasi Sistem Informasi Laporan Diskominfo Dan Sandi Aceh,†J-INTECH: Journal Of Information Technology, vol. 4, no. 1, pp. 1–15, Feb. 2023, doi: 10.22373/j-intech.v4i1.2409.
A. Ebunoluwa and A. James, “AI-Powered Honeypots: Enhancing Deception Technologies for Cyber Defense,†Jun. 2025.
M. B. -, “AI-enhanced Honeypots for Zero-Day Exploit Detection and Mitigation,†International Journal For Multidisciplinary Research, vol. 6, no. 6, Dec. 2024, doi: 10.36948/ijfmr.2024.v06i06.32866.
Z. Zhang et al., “Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space,†2025. [Online]. Available: https://arxiv.org/abs/2505.15778
