Analisis Keamanan Jaringan pada Infrastruktur Cloud Computing Menggunakan Metode Intrusion Detection System

Abstract

The advancement of cloud computing technology has significantly improved data management, information storage, and operational efficiency across industrial and educational sectors. However, the increased adoption of cloud infrastructure introduces critical security challenges, including Distributed Denial of Service (DDoS) attacks, malware, unauthorized access, and data breaches. This study aims to analyze network security levels within cloud computing infrastructure by implementing an Intrusion Detection System (IDS) to detect potential threats. An experimental approach was applied through simulated attacks in a virtual server-based cloud environment. The IDS utilized in this research is Snort, configured to identify various network attacks such as port scanning, brute force attempts, and traffic anomalies. Data were collected through network traffic monitoring during the testing period and analyzed based on detection accuracy, the number of identified attacks, and system response time. The results indicate that IDS implementation significantly enhances network security, achieving a detection accuracy of 93.5%. Additionally, the system provides early warnings of suspicious activities, enabling faster mitigation by network administrators. The effectiveness of the IDS is influenced by rule configuration and monitoring quality. This study concludes that IDS is an effective solution for strengthening cloud network security and minimizing risks to data integrity and service reliability.