  This paper proposes an upgraded electro-magnetic side-channel attack that
automatically reconstructs the intercepted data. A novel system is introduced,
running in parallel with leakage signal interception and catching compromising
data in real-time. Based on deep learning and character recognition the
proposed system retrieves more than 57% of characters present in intercepted
signals regardless of signal type: analog or digital. The approach is also
extended to a protection system that triggers an alarm if the system is
compromised, demonstrating a success rate over 95%. Based on software-defined
radio and graphics processing unit architectures, this solution can be easily
deployed onto existing information systems where information shall be kept
secret.
