Distributed environments are heavily used by nowadays data-intensive software systems to process continuous flows of data produced by a large number of devices (smartphones, IoT, cameras, etc.). While growing complexity, these distributed systems are required to mitigate two key concerns: security and energy. On the one hand, when offloading data processing to the cloud, the application may require security guarantees from the cloud providers in order to avoid privacy and security leaks. On the other hand, the cloud provider aims at continuously improving the energy efficiency of the cloud infrastructure by optimizing the resource usage. This PhD thesis therefore explores the security/energy trade-offs and optimizations that can be considered when deploying data-intensive software systems in distributed environments. In particular, this PhD thesis aims at exploiting all the possible levers that maximize the security of a data-intensive system while minimizing its power consumption.