ANALISIS SERANGAN CYBER MENGGUNAKAN HONEYPOT PADA WEB BERBASIS CLOUD
Article Sidebar
📅
Published:
Sep 10, 2023
Main Article Content
Abstract
Article Summary
Cloud computing has a fairly high-security system, however as it can be accessed from anywhere via the internet network, it does not rule out the possibility that the system is safe from cyberattacks, such as Port Scanning, Brute Force Attacks, Malware Attacks, and other types of cyberattacks, T-Pot Honeypot is an all in one system from Honeypot which is an additional security system to detect, trap attacks not to be able to enter the main system. Based on the research results, the implementation of this T-Pot Honeypot can detect attacks and successfully trap attackers by providing false information such as a list of open ports that are the target of the attacker's search. The log data of the detected attack results are processed by the Honeypot system and forwarded into graphs and diagrams that can be seen through the Kibana Dashboard, making it easier for administrators to monitor attack anomalies carried out by attackers so that they can be used to improve security further.
Keywords
Article Keywords
Downloads
Download data is not yet available.
Article Details
How to Cite
Pamungkas, B. S., & Sembiring, I. (2023). ANALISIS SERANGAN CYBER MENGGUNAKAN HONEYPOT PADA WEB BERBASIS CLOUD. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 4(3), 1284-1295. https://doi.org/10.35870/jimik.v4i3.325
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 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 a Creative Commons Attribution License (CC-BY 4.0) that allows others to share the work with an acknowledgement 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 acknowledgement 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.
License: All articles are licensed under 
References
Nadeem, M., Arshad, A., Riaz, S., Band, S. S., & Mosavi, A. (2021). Intercept the cloud network from brute force and DDoS attacks via intrusion detection and prevention system. IEEE Access, 9, 152300-152309. DOI: 10.1109/ACCESS.2021.3126535.
Benyamin, J., Mualim, M., & Duarte, E. P. (2023). MANAJEMEN RISIKO KEAMANAN INFORMASI DALAM MEMINIMALISASI ANCAMAN SIBER PADA PUSAT DATA DAN TEKNOLOGI INFORMASI KOMUNIKASI BADAN SIBER DAN SANDI NEGARA GUNA MENINGKATKAN PERTAHANAN DAN KEAMANAN SIBER. Manajemen Pertahanan: Jurnal Pemikiran dan Penelitian Manajemen Pertahanan, 9(1).
Park, J., Kim, J., Gupta, B. B., & Park, N. (2021). Network log-based SSH brute-force attack detection model. Computers, Materials & Continua, 68(1).
Alam, S., & Kunang, Y. N. (2021). Analisis Serangan Brute Force Pada Ip Address Cctv (Closed Circuit Television) Menggunakan Metode Komputer Forensic. In Bina Darma Conference on Computer Science (BDCCS) (Vol. 3, No. 3, pp. 544-553).
Widiyanto, W. W. (2022). SIMRS Network Security Simulation Using Snort IDS and IPS Methods. Indonesian of Health Information Management Journal (INOHIM), 10(1), 10-17. DOI: https://doi.org/10.47007/inohim.v10i1.396.
TAŞÇI, H., Gönen, S., BARIŞKAN, M. A., KARACAYILMAZ, G., Alhan, B., & YILMAZ, E. N. (2021). Password Attack Analysis Over Honeypot Using Machine Learning Password Attack Analysis. Turkish Journal of Mathematics and Computer Science, 13(2), 388-402.
Amal, M. R., & Venkadesh, P. (2022). Review of cyber attack detection: Honeypot system. Webology, 19(1), 5497-5514.
Muhammad, R. M., Irawati, I. D., & Iqbal, M. (2021). Implementasi Sistem Keamanan Jaringan Lokal Menggunakan Honeypot Dionaea, Dan Ids, Serta Analisis Malware Menggunakan Malware Analysis System. eProceedings of Applied Science, 7(3).
Shivathmika, N., Divya, A., Lakshmi, K. A., & Manikandan, M. L. Intrusion Detection and Prevention Using Honeypot Network for Cloud Security.
Wanjau, S. K., Wambugu, G. M., & Kamau, G. N. (2021). SSH-brute force attack detection model based on deep learning.
Prakoso, R. D. Y. (2022). IMPLEMENTASI LOW INTERACTION HONEYPOT DAN PORT KNOCKING UNTUK MENINGKATKAN KEAMANAN JARINGAN. Perwira Journal of Science & Engineering, 2(1), 16-23. DOI: https://doi.org/10.54199/pjse.v2i1.96.
Duha, T., Setiawan, W., & Fajriyah, N. (2022). Analisis Layanan Cloud Computing Di Era Digital. Jurnal Informatika, 1(1), 32-39. DOI: https://doi.org/10.57094/ji.v1i1.355.
NURILAHI, D. K., MUNADI, R., SYAHRIAL, S., & Bahri, A. L. (2022). Penerapan Metode Naïve Bayes pada Honeypot Dionaea dalam Mendeteksi Serangan Port Scanning. ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, 10(2), 309. DOI: https://doi.org/10.26760/elkomika.v10i2.309.
Mulyanto, Y., Herfandi, H., & Kirana, R. C. (2022). Analisis Keamanan Wireless Local Area Network (Wlan) Terhadap Serangan Brute Force Dengan Metode Penetration Testing (Studi Kasus: Rs H. Lmanambai Abdulkadir). Jurnal Informatika Teknologi dan Sains (Jinteks), 4(1), 26-35. DOI: https://doi.org/10.51401/jinteks.v4i1.1528.
Shurman, M. M., Khrais, R. M., & Yateem, A. A. (2020). DoS and DDoS attack detection using deep learning and IDS. Int. Arab J. Inf. Technol., 17(4A), 655-661.
Putra, T. H. (2021). IMPLEMENTASI PORT KNOCKING DAN TPOT HONEYPOT PADA PRIVATE CLOUD SERVER SEBAGAI PENDETEKSI SERANGAN DALAM JARINGAN (Doctoral dissertation, Universitas Muhammadiyah Malang).
Varma, P., Siddiqui, A., Vadher, P., & Baloda, V. (2020). Snort IDPS using Raspberry Pi 4. International Journal of Engineering Research Technology (IJERT), 9.
Dermawati, R., & Siregar, M. H. (2020). Implementasi Honeypot Pada Jaringan Internet Labor Fakultas Teknik UNIKS Menggunakan Dionaea Sebagai Keamanan Jaringan. Jurnal Ilmiah Edutic: Pendidikan dan Informatika, 7(1), 20-30. DOI: https://doi.org/10.21107/edutic.v7i1.8660.
Benyamin, J., Mualim, M., & Duarte, E. P. (2023). MANAJEMEN RISIKO KEAMANAN INFORMASI DALAM MEMINIMALISASI ANCAMAN SIBER PADA PUSAT DATA DAN TEKNOLOGI INFORMASI KOMUNIKASI BADAN SIBER DAN SANDI NEGARA GUNA MENINGKATKAN PERTAHANAN DAN KEAMANAN SIBER. Manajemen Pertahanan: Jurnal Pemikiran dan Penelitian Manajemen Pertahanan, 9(1).
Park, J., Kim, J., Gupta, B. B., & Park, N. (2021). Network log-based SSH brute-force attack detection model. Computers, Materials & Continua, 68(1).
Alam, S., & Kunang, Y. N. (2021). Analisis Serangan Brute Force Pada Ip Address Cctv (Closed Circuit Television) Menggunakan Metode Komputer Forensic. In Bina Darma Conference on Computer Science (BDCCS) (Vol. 3, No. 3, pp. 544-553).
Widiyanto, W. W. (2022). SIMRS Network Security Simulation Using Snort IDS and IPS Methods. Indonesian of Health Information Management Journal (INOHIM), 10(1), 10-17. DOI: https://doi.org/10.47007/inohim.v10i1.396.
TAŞÇI, H., Gönen, S., BARIŞKAN, M. A., KARACAYILMAZ, G., Alhan, B., & YILMAZ, E. N. (2021). Password Attack Analysis Over Honeypot Using Machine Learning Password Attack Analysis. Turkish Journal of Mathematics and Computer Science, 13(2), 388-402.
Amal, M. R., & Venkadesh, P. (2022). Review of cyber attack detection: Honeypot system. Webology, 19(1), 5497-5514.
Muhammad, R. M., Irawati, I. D., & Iqbal, M. (2021). Implementasi Sistem Keamanan Jaringan Lokal Menggunakan Honeypot Dionaea, Dan Ids, Serta Analisis Malware Menggunakan Malware Analysis System. eProceedings of Applied Science, 7(3).
Shivathmika, N., Divya, A., Lakshmi, K. A., & Manikandan, M. L. Intrusion Detection and Prevention Using Honeypot Network for Cloud Security.
Wanjau, S. K., Wambugu, G. M., & Kamau, G. N. (2021). SSH-brute force attack detection model based on deep learning.
Prakoso, R. D. Y. (2022). IMPLEMENTASI LOW INTERACTION HONEYPOT DAN PORT KNOCKING UNTUK MENINGKATKAN KEAMANAN JARINGAN. Perwira Journal of Science & Engineering, 2(1), 16-23. DOI: https://doi.org/10.54199/pjse.v2i1.96.
Duha, T., Setiawan, W., & Fajriyah, N. (2022). Analisis Layanan Cloud Computing Di Era Digital. Jurnal Informatika, 1(1), 32-39. DOI: https://doi.org/10.57094/ji.v1i1.355.
NURILAHI, D. K., MUNADI, R., SYAHRIAL, S., & Bahri, A. L. (2022). Penerapan Metode Naïve Bayes pada Honeypot Dionaea dalam Mendeteksi Serangan Port Scanning. ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, 10(2), 309. DOI: https://doi.org/10.26760/elkomika.v10i2.309.
Mulyanto, Y., Herfandi, H., & Kirana, R. C. (2022). Analisis Keamanan Wireless Local Area Network (Wlan) Terhadap Serangan Brute Force Dengan Metode Penetration Testing (Studi Kasus: Rs H. Lmanambai Abdulkadir). Jurnal Informatika Teknologi dan Sains (Jinteks), 4(1), 26-35. DOI: https://doi.org/10.51401/jinteks.v4i1.1528.
Shurman, M. M., Khrais, R. M., & Yateem, A. A. (2020). DoS and DDoS attack detection using deep learning and IDS. Int. Arab J. Inf. Technol., 17(4A), 655-661.
Putra, T. H. (2021). IMPLEMENTASI PORT KNOCKING DAN TPOT HONEYPOT PADA PRIVATE CLOUD SERVER SEBAGAI PENDETEKSI SERANGAN DALAM JARINGAN (Doctoral dissertation, Universitas Muhammadiyah Malang).
Varma, P., Siddiqui, A., Vadher, P., & Baloda, V. (2020). Snort IDPS using Raspberry Pi 4. International Journal of Engineering Research Technology (IJERT), 9.
Dermawati, R., & Siregar, M. H. (2020). Implementasi Honeypot Pada Jaringan Internet Labor Fakultas Teknik UNIKS Menggunakan Dionaea Sebagai Keamanan Jaringan. Jurnal Ilmiah Edutic: Pendidikan dan Informatika, 7(1), 20-30. DOI: https://doi.org/10.21107/edutic.v7i1.8660.