A Literature Review : Honeypot-Based Security Solutions for Safeguarding Critical Data at BMKG
Main Article Content
Abstract
The expanding dependence on advanced foundations by meteorological organizations like BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) has increased the hazard of cyber attacks, which seem compromise basic climate and climate information frameworks. This paper investigates the execution of honeypot-based security arrangements as a proactive approach to defend BMKG's organize framework. Honeypots, outlined to draw potential aggressors, give important bits of knowledge into rising dangers and offer assistance to relieve dangers some time recently they reach center frameworks. By sending honeypots in BMKG's organize, this consider explores their viability in identifying and analyzing cyber-attacks focusing on meteorological information, which is basic for open security and national improvement arranging. The inquire about presents a comparative investigation of different honeypot arrangements and their capacity to distinguish modern dangers, such as zero-day misuses and Progressed Tireless Dangers (APTs), which posture critical dangers to BMKG's operations. Comes about illustrate that joining honeypots into BMKG's cybersecurity system upgrades risk discovery, diminishes reaction time, and reinforces in general information security. These discoveries highlight the potential for honeypot frameworks to play a key part in securing basic meteorological data, guaranteeing the unwavering quality and astuteness of climate information fundamental for calamity readiness and hazard administration.
Downloads
References
A. Javadpour, F. Ja’fari, T. Taleb, M. Shojafar, and C. Benzaïd, “A comprehensive survey on cyber deception techniques to improve honeypot performance,” May 01, 2024, Elsevier Ltd. doi: 10.1016/j.cose.2024.103792.
S. Kumar, B. Janet, and R. Eswari, “Multi Platform Honeypot for Generation of Cyber Threat Intelligence,” Proceedings of the 2019 IEEE 9th International Conference on Advanced Computing, IACC 2019, pp. 25–29, 2019, doi : 10.1109/IACC48062.2019.8971584.
M. Antunes, M. Maximiano, R. Gomes, and D. Pinto, “Information Security and Cybersecurity Management: A Case Study with SMEs in Portugal,” Journal of Cybersecurity and Privacy, vol. 1, no. 2, pp. 219–238, Jun. 2021, doi: 10.3390/jcp1020012.
M. Sandhya Rani, Guda Ankitha, Polasani Harini, and G Ravi, “Cyber Honeypot,” Int J Sci Res Sci Technol, vol. 11, no. 2, pp. 94–98, Apr. 2024, doi: 10.32628/ijsrst52411168.
MILCOM 2017 2017 IEEE Military Communications Conference (MILCOM). IEEE, 2017.
X. Yang, J. Yuan, H. Yang, Y. Kong, H. Zhang, and J. Zhao, “A Highly Interactive Honeypot-Based Approach to Network Threat Management,” Future Internet, vol. 15, no. 4, Apr. 2023, doi: 10.3390/fi15040127.
S. Saeed, S. A. Suayyid, M. S. Al-Ghamdi, H. Al Muhaisen, and A. M. Almuhaideb, “A Systematic Literature Review on Cyber Threat Intelligence for Organizational Cybersecurity Resilience,” Aug. 01, 2023, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/s23167273
F. N. Motlagh, M. Hajizadeh, M. Majd, P. Najafi, F. Cheng, and C. Meinel, “Large Language Models in Cybersecurity: State-of-the-Art,” Jan. 2024, [Online]. Available: http://arxiv.org/abs/2402.00891
S. Kumar, B. Janet, and R. Eswari, “Multi Platform Honeypot for Generation of Cyber Threat Intelligence,” in Proceedings of the 2019 IEEE 9th International Conference on Advanced Computing, IACC 2019, Institute of Electrical and Electronics Engineers Inc., Dec. 2019, pp. 25–29. doi: 10.1109/IACC48062.2019.8971584.
A. P. Zhao, Q. Zhang, M. Alhazmi, P. J. H. Hu, S. Zhang, and X. Yan, “AI for science: Covert cyberattacks on energy storage systems,” J Energy Storage, vol. 99, p. 112835, Oct. 2024, doi: 10.1016/J.EST.2024.112835.
W. Fan, Z. Du, M. Smith-Creasey, and D. Fernandez, “HoneyDOC: An Efficient Honeypot Architecture Enabling All-Round Design,” IEEE Journal on Selected Areas in Communications, vol. 37, no. 3, pp. 683–697, 2019, doi: 10.1109/JSAC.2019.2894307.
ICCSP : 2017 International Conference on Communication and Signal Processing : 6-8 April 2017. IEEE, 2018.
A. S. Sani, E. Bertino, D. Yuan, K. Meng, and Z. Y. Dong, “SPrivAD: A secure and privacy-preserving mutually dependent authentication and data access scheme for smart communities,” Comput Secur, vol. 115, p. 102610, Apr. 2022, doi: 10.1016/J.COSE.2022.102610.
A. Girdhar and S. Kaur, “Comparative Study of Different Honeypots System,” 2012. [Online]. Available: www.ijerd.com
P. Lanka, K. Gupta, and C. Varol, “Intelligent Threat Detection—AI-Driven Analysis of Honeypot Data to Counter Cyber Threats,” Electronics (Switzerland), vol. 13, no. 13,. Jul. 2024, doi: 10.3390/electronics13132465.
W. Zhang, B. Zhang, Y. Zhou, H. He, and Z. Ding, “An IoT Honeynet Based on Multiport Honeypots for Capturing IoT Attacks,” IEEE Internet Things J, vol. 7, no. 5, pp. 3991–3999, May 2020, doi: 10.1109/JIOT.2019.2956173.
W. Tian, M. Du, X. Ji, G. Liu, Y. Dai, and Z. Han, “Honeypot Detection Strategy against Advanced Persistent Threats in Industrial Internet of Things: A Prospect Theoretic Game,” IEEE Internet Things J, vol. 8, no. 24, pp. 17372–17381, Dec. 2021, doi: 10.1109/JIOT.2021.3080527.
L. Shi, Y. Li, and H. Feng, “Performance analysis of honeypot with Petri nets,” Information (Switzerland), vol. 9, no. 10, 2018, doi: 10.3390/info9100245..
W. Zhang, B. Zhang, Y. Zhou, H. He, and Z. Ding, “An IoT Honeynet Based on Multiport Honeypots for Capturing IoT Attacks,” IEEE Internet Things J, vol. 7, no. 5, pp. 3991–3999, 2020, doi: 10.1109/JIOT.2019.2956173.
W. Fan, Z. Du, D. Fernandez, and V. A. Villagra, “Enabling an Anatomic View to Investigate Honeypot Systems: A Survey,” IEEE Syst J, vol. 12, no. 4, pp. 3906–3919, Dec. 2018, doi: 10.1109/JSYST.2017.2762161.
Article Sidebar
