Wide Area Measurement Systems (WAMSs) are used in power networks to improve the situational awareness of the operator, as well as to facilitate real-time control and protection decisions. In WAMSs, Phasor Data Concentrators (PDCs) collect time-synchronized data of Phasor Measurement Units (PMUs) through the communication system, and direct it to the control center to be used in wide-area control and protection applications. Due to the dependence of WAMSs on information and communication technologies, cyber-attacks can target these systems and propagate through them, i.e., infect a greater number of components by accessing and controlling a few of them. On this basis, this paper initially develops a Learning-Based Framework (LBF) to estimate the required defense strategy to counter the propagation of cyber-attacks in WAMSs. Afterwards, through solving a linear Binary Integer Programming (BIP) problem, this paper develops a mitigation strategy to optimally reconfigure the communication network and reduce the contamination probability for critical PMUs and PDCs while maintaining the observability of the grid. The simulation results obtained from IEEE 14- and 30-bus test systems corroborate the effectiveness of the proposed LBF and communication network reconfiguration strategy in mitigating the propagation of cyber-attacks in WAMSs.