Security problems have emerged as soon as computers and networks entered our life and started to hold sensitive information. However network security of teams of vehicles still remains an open research problem despite its vital importance. This is because networked systems are difficult to observe and control even by expert users. Game theory provides an excellent framework to study network security problems because it captures the interlock between defensive and offensive algorithms. Network security can be viewed as a strategic game played between malicious attackers that manipulate data or compromise functionality and defenders whose aim is to protect information and maintain proper service operation. The security game framework is applicable to security problems in a variety of areas ranging from intrusion detection to social, wireless, and vehicular networks. This chapter introduces two different types of attacks (threats). Namely we consider measurement (vehicle trajectory deviation) and jamming attacks compromising the security of the networked teams. We propose two new techniques based on reinforcement learning to guarantee desired behavior in the presence of those attacks.