<![CDATA[Various cyberattack threats are sophisticated and reliable detection approaches, as complex and rampant as they are. One outstanding approach is the use of Honeynet, a network simulator that simulates real networks for analysis and detection purposes. This study aims to compare the effectiveness of Honeynet in detecting spyware with alternative detection methods. We conducted experiments where we implemented Honeynet in a simulated network environment that breaks the real network infrastructure. Other detection methods we reference include intrusion detection systems (IDS) based on hands and behaviour. In addition, we also analysed the types of spam most frequently detected by Honeynet. We can identify the most common trends and their characteristics by analysing the attack test results. The research findings show that Honeynet is very effective in detecting certain cyberattacks, especially zero-day attacks and attacks that use new methods that have not been detected by known signatures. However, we also found that behaviour-based detection methods tend to be more effective in detecting attacks that are novel and unexpected]]>
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