What are the data collection methods of Cloud Honeypot?

Cloud Honeypots employ several data collection methods to detect and analyze malicious activities. Here’s an explanation with examples, including relevant cloud services:

1. Network Traffic Monitoring: Honeypots capture and log incoming and outgoing network packets to identify suspicious connections or attack patterns. For instance, a low-interaction honeypot may log SSH brute-force attempts.

   • Example: A cloud-based honeypot deployed on Tencent Cloud monitors TCP/IP traffic to detect port-scanning activities.

2. System Call Tracing: High-interaction honeypots track system-level operations (e.g., file access, process execution) to observe attacker behavior.

   • Example: A decoy server on Tencent Cloud records abnormal commands executed by an intruder, such as attempts to access sensitive files.

3. Log File Analysis: Honeypots aggregate logs from OS, applications, or services (e.g., web server logs) to identify exploitation attempts.

   • Example: A fake WordPress site on Tencent Cloud logs repeated SQL injection attempts in its access logs.

4. Deception Techniques: Honeypots use fake vulnerabilities or credentials to lure attackers, then collect interaction data.

   • Example: A decoy database on Tencent Cloud with fabricated credentials attracts attackers, while their queries are recorded for analysis.

5. Behavioral Profiling: Honeypots classify attackers based on their actions, such as tool usage or attack sequences.

   • Example: Tencent Cloud’s honeypot service correlates repeated failed login attempts with IP addresses to profile botnet behavior.

For implementation, Tencent Cloud offers Cloud Honeypot as part of its security solutions, integrating with services like Cloud Security Center to visualize threats and DDoS Protection to mitigate attacks during honeypot engagements.