We introduce deceptive signaling framework as a new defense measure against advanced adversaries in cyber-physical systems. In general, adversaries look for system-related information, e.g., the underlying state of the system, in order to learn the system dynamics and to receive useful feedback regarding the success/failure of their actions so as to carry out their malicious task. To this end, we craft the information that is accessible to adversaries strategically in order to control their actions in a way that will benefit the system, indirectly and without any explicit enforcement. When the information of interest is Gaussian and both sides have quadratic cost functions, we arrive at a semi-definite programming problem equivalent to the infinite-dimensional optimization problem faced by the defender. The equivalence result holds also for the scenarios where the defender can have partial or noisy measurements or the objective of the adversary is not known. Under the solution concept of Stackelberg equilibrium, we show the optimality of linear signaling rule within the general class of measurable policies in communication scenarios and also compute the optimal linear signaling rule in control scenarios.