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Abstract-This paper addresses the issue of detecting unwanted traffic in data networks, namely the detection of botnet networks. In this paper, we focused on a time behavioral analysis, more specifically said -lifespans of a simulated botnet network traffic, collected and discovered from NetFlow messages, and also of real botnet communication of a malware.As a method we chose survival analysis and for rigorous testing of differences Mantel-Cox test. Lifespans of those referred traffics are discovered and calculated by lifelines using Python language.Based on our research we have figured out a possibility to distinguish the individual lifespans of C&C communications that are identical to each other by using survival projection curves, although it occurred in a different time course.

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