Seiring meningkatnya kompleksitas jaringan serta tingginya ketergantungan pada perangkat infrastruktur jaringan, serangan siber terhadap sistem yang terhubung langsung ke internet menjadi tantangan utama dalam pengelolaan keamanan infrastruktur. Eksploitasi pada protokol umum layanan publik seperti SSH, Telnet, SMB, dan FTP sering dimanfaatkan oleh aktor siber untuk menyusup ke sistem menggunakan kredensial lemah atau default. Penelitian ini mengusulkan pendekatan proaktif melalui pemanfaatan honeypot sebagai alat pendeteksi serangan dengan mengimplementasikan sistem yang rentan terhadap eksploitasi. Arsitektur pengujian dirancang dalam dua skenario, yaitu farm server pada virtual (vServer) dan perangkat router, yang masing-masing dilengkapi dengan honeypot jenis Cowrie, Dionaea, Honeytrap, Suricata, dan Mailoney. Serangkaian teknik analisis diterapkan, seperti Statistical Traffic Analysis, identifikasi layanan target dan protokol, pemantauan port SSH, deteksi intrusi berbasis jaringan (IDS), serta analisis sampel malware yang berhasil ditangkap. Data log yang dikumpulkan selama dua bulan mencerminkan aktivitas serangan yang cukup tinggi, dengan total catatan sebanyak 2.813.776 entri dari Cowrie, 2.109.900 dari Dionaea, 1.047.814 dari Honeytrap, dan 650.741 dari Suricata. Selain pemantauan serangan, penelitian ini juga mengembangkan mekanisme pertahanan dengan mengintegrasikan pemfilteran otomatis berbasis IPTables. Pendekatan ini terbukti mampu mengurangi beban kerja perangkat jaringan, dengan efisiensi hingga 45% (CPU dan Memory) pada perangkat Router dan sekitar 40% (CPU dan Memory) pada Server Farm. Hasil penelitian ini menunjukkan bahwa penggabungan berbagai jenis honeypot dengan dukungan otomasi mitigasi berbasis filtering firewall iptables mampu meningkatkan deteksi dini dan memperkuat ketahanan jaringan terhadap serangan dari internet. Abstract As the complexity of networks increases and the high dependence on network infrastructure devices, cyber attacks on systems directly connected to the internet become a major challenge in managing infrastructure security. Exploits on common public service protocols such as SSH, Telnet, SMB, and FTP are often used by cyber actors to infiltrate systems using weak or default credentials. This study proposes a proactive approach through the use of honeypots as an attack detection tool by implementing a system that is vulnerable to exploitation. The testing architecture is designed in two scenarios, namely a virtual server farm (vServer) and a router device, each equipped with a honeypot type Cowrie, Dionaea, Honeytrap, Suricata, and Mailoney. A series of analysis techniques are applied, such as Statistical Traffic Analysis, identification of target services and protocols, SSH port monitoring, network-based intrusion detection (IDS), and analysis of successfully captured malware samples. The log data collected over two months reflects quite high attack activity, with a total of 2,813,776 entries from Cowrie, 2,109,900 from Dionaea, 1,047,814 from Honeytrap, and 650,741 from Suricata. In addition to monitoring attacks, this study also developed a defense mechanism by integrating IPTables-based automatic filtering. This approach has been proven to be able to reduce the workload of network devices, with an efficiency of up to 45% (CPU and Memory) on Router devices and around 40% (CPU and Memory) on Server Farms. The results of this study indicate that combining various types of honeypots with the support of iptables firewall filtering-based mitigation automation can improve early detection and strengthen network resilience against attacks from the internet.
English
Seiring meningkatnya kompleksitas jaringan serta tingginya ketergantungan pada perangkat infrastruktur jaringan, serangan siber terhadap sistem yang terhubung langsung ke internet menjadi tantangan utama dalam pengelolaan keamanan infrastruktur. Eksploitasi pada protokol umum layanan publik seperti SSH, Telnet, SMB, dan FTP sering dimanfaatkan oleh aktor siber untuk menyusup ke sistem menggunakan kredensial lemah atau default. Penelitian ini mengusulkan pendekatan proaktif melalui pemanfaatan honeypot sebagai alat pendeteksi serangan dengan mengimplementasikan sistem yang rentan terhadap eksploitasi. Arsitektur pengujian dirancang dalam dua skenario, yaitu farm server pada virtual (vServer) dan perangkat router, yang masing-masing dilengkapi dengan honeypot jenis Cowrie, Dionaea, Honeytrap, Suricata, dan Mailoney. Serangkaian teknik analisis diterapkan, seperti Statistical Traffic Analysis, identifikasi layanan target dan protokol, pemantauan port SSH, deteksi intrusi berbasis jaringan (IDS), serta analisis sampel malware yang berhasil ditangkap. Data log yang dikumpulkan selama dua bulan mencerminkan aktivitas serangan yang cukup tinggi, dengan total catatan sebanyak 2.813.776 entri dari Cowrie, 2.109.900 dari Dionaea, 1.047.814 dari Honeytrap, dan 650.741 dari Suricata. Selain pemantauan serangan, penelitian ini juga mengembangkan mekanisme pertahanan dengan mengintegrasikan pemfilteran otomatis berbasis IPTables. Pendekatan ini terbukti mampu mengurangi beban kerja perangkat jaringan, dengan efisiensi hingga 45% (CPU dan Memory) pada perangkat Router dan sekitar 40% (CPU dan Memory) pada Server Farm. Hasil penelitian ini menunjukkan bahwa penggabungan berbagai jenis honeypot dengan dukungan otomasi mitigasi berbasis filtering firewall iptables mampu meningkatkan deteksi dini dan memperkuat ketahanan jaringan terhadap serangan dari internet. Abstract As the complexity of networks increases and the high dependence on network infrastructure devices, cyber attacks on systems directly connected to the internet become a major challenge in managing infrastructure security. Exploits on common public service protocols such as SSH, Telnet, SMB, and FTP are often used by cyber actors to infiltrate systems using weak or default credentials. This study proposes a proactive approach through the use of honeypots as an attack detection tool by implementing a system that is vulnerable to exploitation. The testing architecture is designed in two scenarios, namely a virtual server farm (vServer) and a router device, each equipped with a honeypot type Cowrie, Dionaea, Honeytrap, Suricata, and Mailoney. A series of analysis techniques are applied, such as Statistical Traffic Analysis, identification of target services and protocols, SSH port monitoring, network-based intrusion detection (IDS), and analysis of successfully captured malware samples. The log data collected over two months reflects quite high attack activity, with a total of 2,813,776 entries from Cowrie, 2,109,900 from Dionaea, 1,047,814 from Honeytrap, and 650,741 from Suricata. In addition to monitoring attacks, this study also developed a defense mechanism by integrating IPTables-based automatic filtering. This approach has been proven to be able to reduce the workload of network devices, with an efficiency of up to 45% (CPU and Memory) on Router devices and around 40% (CPU and Memory) on Server Farms. The results of this study indicate that combining various types of honeypots with the support of iptables firewall filtering-based mitigation automation can improve early detection and strengthen network resilience against attacks from the internet.
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