Efektivitas Honeynet dalam Mendeteksi Serangan Siber
DOI:
https://doi.org/10.54259/satesi.v4i1.2658Keywords:
Honeynet, IDS, Zero-DayAbstract
Various cyberattack threats are sophisticated and reliable detection approaches, as complex and rampant as they are. One outstanding approach is the use of Honeynet, a network simulator that simulates real networks for analysis and detection purposes. This study aims to compare the effectiveness of Honeynet in detecting spyware with alternative detection methods. We conducted experiments where we implemented Honeynet in a simulated network environment that breaks the real network infrastructure. Other detection methods we reference include intrusion detection systems (IDS) based on hands and behaviour. In addition, we also analysed the types of spam most frequently detected by Honeynet. We can identify the most common trends and their characteristics by analysing the attack test results. The research findings show that Honeynet is very effective in detecting certain cyberattacks, especially zero-day attacks and attacks that use new methods that have not been detected by known signatures. However, we also found that behaviour-based detection methods tend to be more effective in detecting attacks that are novel and unexpected
Downloads
References
I. R. Putranti, A. Amaliyah, and R. Windiani, “Smartcity : Model Ketahanan Siber Untuk Usaha Kecil Dan Menengah,” Jurnal Ketahanan Nasional, vol. 26, no. 3, p. 359, Dec. 2020, doi: 10.22146/jkn.57322.
J. Ren, C. Zhang, and Q. Hao, “A theoretical method to evaluate honeynet potency,” Future Generation Computer Systems, vol. 116, pp. 76–85, 2021, doi: https://doi.org/10.1016/j.future.2020.08.021.
J. Franco, A. Aris, B. Canberk, and A. S. Uluagac, “A Survey of Honeypots and Honeynets for Internet of Things, Industrial Internet of Things, and Cyber-Physical Systems,” IEEE Communications Surveys & Tutorials, vol. 23, no. 4, pp. 2351–2383, Jun. 2021, doi: 10.1109/COMST.2021.3106669.
M. Research, C. Security, J. P. John, and I. Khan, “Novel Technique for Detecting Unknown Threats Using Honeynet Instead of Purple Teaming in Organizations.” Accessed: Jun. 06, 2024. [Online]. Available: https://norma.ncirl.ie/6524/1/jithinpauljohn.pdf
A. Nugraha and F. Adi Rafrastara, “BOTNET DETECTION SURVEY,” 2011. Accessed: Jun. 02, 2024. [Online]. Available: https://publikasi.dinus.ac.id/index.php/semantik/article/view/234
J. A. Attoh, “Security Measures Against Malware, Botnets & Ransomware,” Advances in Multidisciplinary and scientific Research Journal Publication, vol. 1, no. 1, pp. 345–352, Jul. 2022, doi: 10.22624/AIMS/CRP-BK3-P55.
Ajit Wagh, Ravindra Pawar, Nilesh Wable, Sanket Wandhekar, and Prof. M. S. Dighe, “Detection of Cyber Attacks and Network Attacks using Machine Learning Algorithms,” International Journal of Advanced Research in Science, Communication and Technology, pp. 414–417, Apr. 2024, doi: 10.48175/ijarsct-18161.
J. Franco, A. Aris, B. Canberk, and A. S. Uluagac, “A Survey of Honeypots and Honeynets for Internet of Things, Industrial Internet of Things, and Cyber-Physical Systems,” IEEE Communications Surveys & Tutorials, vol. 23, no. 4, pp. 2351–2383, Jun. 2021, doi: 10.1109/COMST.2021.3106669.
F. Mayorga, J. Vargas, E. Álvarez, and H. D. Martinez, “Honeypot Network Configuration through Cyberattack Patterns,” in 2019 International Conference on Information Systems and Computer Science (INCISCOS), Nov. 2019, pp. 150–155. doi: 10.1109/INCISCOS49368.2019.00032.
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, 2024, doi: https://doi.org/10.1016/j.cose.2024.103792.
H. Setiawan, M. Agus Munandar, L. W. Astuti, and P. Korespondensi, “PENGGUNAAN METODE SIGNATURED BASED DALAM PENGENALAN POLA SERANGAN DI JARINGAN KOMPUTER,” vol. 8, no. 3, pp. 517–524, 2021, doi: 10.25126/jtiik.202184200.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Sugiyatno Sugiyatno, Didik Setiyadi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).