Abstract: Large networks that change dynamically over time are ubiquitous in various areas such as social networks, and epidemiology. These networks are often modeled by random dynamics which, despite being relatively simple, give a quite accurate macroscopic description of real networks. In "network archaeology" one studies statistical problems of inferring the past properties of such growing networks, given the current state of the network. In this talk we discuss some simple network models and review recent results on revealing the past of the networks.