ANALISIS SERANGAN CYBER MENGGUNAKAN HONEYPOT PADA WEB BERBASIS CLOUD
Original Full-Text Article
Download published version for reading and archivingAbstract
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.
Author Biographies
Program Studi Teknik Infomatika, Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Kota Salatiga, Provinsi Jawa Tengah, Indonesia
Program Studi Teknik Infomatika, Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Kota Salatiga, Provinsi Jawa Tengah, Indonesia
How to Cite
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .
- Share: You are free to copy, distribute, and transmit the work in any medium or format.
- Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
- Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
References
Total: 18 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.
Similar Articles
Articles sharing related keywords and machine learning classifications: