<![CDATA[Network security is a crucial issue in the rapidly developing era of information technology. One of the main threats is malware, which is malicious software that harms systems and data. To solve this problem, analysis and detection of malware on network protocols need to be improved using effective methods. This research explores the application of two main methods, namely static and dynamic malware analysis. First, static malware analysis involves examining malware files without running them. This method includes analysis of signatures, heuristics, and malicious code to identify typical malware patterns in files on the network.Second, dynamic malware analysis executes malware in an isolated environment (sandbox) to monitor its behavior and impact on the system. This process allows detection of malicious changes and attempts by malware to propagate itself. By combining these two methods, a holistic and efficient approach in malware detection on network protocols can be achieved. It is hoped that the results of this research can improve network security, protect infrastructure from ever-evolving malware threats. The use of static and dynamic analysis methods will help deal with increasingly complex security challenges, enabling networks to operate more securely and reliably.]]>
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