Passive Internet monitoring is a powerful tool for measuring and characterizing interesting network activity like worms or distributed denial of service attacks. By employing statistical analysis on the captured network traffic, Internet threat monitors gain valuable insight into the nature of Internet threats. In the past, these monitors have been successfully used not only to detect DoS attacks or worm outbreaks but also to monitor worm propagation trends and other malicious activities on the Internet. Today, passive Internet threat monitors are widely recognized as an important technology for detecting and understanding anomalies on the Internet in a macroscopic way.

Unfortunately, monitors that publish their results on the Internet provide a feedback loop that can be used by adversaries to deduce a monitor’s sensor locations. Knowledge of a monitor’s sensor location can severely reduce its functionality as the captured data may have been tampered with and can no longer be trusted. This paper describes algorithms for detecting which address spaces an Internet threat monitor listens to and presents empirical evidences that they are successful in locating the sensor positions of monitors deployed on the Internet. We also present solutions to make passive Internet threat monitors" harder to detect".