Nowadays virtualization is used as the sole mechanism to isolate different users on Cloud platforms. We will show that due to improper virtualization of micro-architectural components, data leak and modification can occur on public Clouds. Furthermore, using the same vector, it is possible to induce performance interferences, i.e. noisy neighbors. Using this approach, a VM can slow down and steal resources from concurrent VMs. We propose placement heuristics that take into account isolation requirements. We modify three classical heuristics to take into account these requirements. Furthermore, we propose four new heuristics that take into account the hierarchy of the Cloud platforms and the isolation requirements. Finally, we evaluate these heuristics and compare them with the modified classical ones. We show that our heuristics are performing at least as good as classical ones but are scaling better and are faster by a few order of magnitude than the classical ones.