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Recent stealth attacks cleverly disguise malicious activities, masquerading as ordinary connections to popular online services through seemingly innocuous applications. These methods often evade detection by traditional network monitoring or signature-based techniques, as attackers frequently hide Command and Control (C&#x0026;C) servers within well-known cloud service providers, making the traffic anomalies appear normal. In this paper, we introduce an application-level monitoring system,  Anteater .  Anteater  constructs a detailed profile for each legitimate software&#x2019;s network traffic behavior, outlining the  expected  traffic patterns. By scrutinizing a program&#x2019;s network traffic configuration,  Anteater  efficiently pinpoints and intercepts the IP addresses associated with abnormal program access. Implemented in a real-world enterprise environment,  Anteater  was tested on a dataset containing over 400 million real-world network traffic sessions. The evaluation results demonstrate that  Anteater  achieves a high detection rate for malware injections, boasting a true positive rate of 94.5% and a false positive rate of less than 0.1%.

Anteater: Advanced Persistent Threat Detection with Program Network Traffic Behavior