Millimeter wave systems leverage beamforming to generate narrow, high-powered beams for overcoming the increased path loss in the millimeter wave spectrum. These beams are spa- tially confined, making millimeter wave links more resilient to eavesdropping and jamming attacks. However, the millimeter wave radios locate each other and establish communica- tion by exhaustively probing all possible angular directions, increasing their susceptibility to attacks. In this thesis, we showcase a secure beam management solution where we apply an adaptive beam management procedure that avoids probing the directions of potential attackers. We employ a reinforcement learning agent to control the probing and dynami- cally restrict sweeps to a subset of beams in the millimeter wave transmitter codebook to avoid the locations of potential attackers based on a proposed metric that quantifies the beam sweeping secrecy over a pre-defined area. We evaluate our proposed system through numerical simulations and an experimental real-life implementation on the CCI xG Testbed. / Master of Science / Millimeter wave systems leverage beamforming, a technique that's used to direct both trans- mission and reception of a signal to create narrow, high-powered beams that can overcome the signal deterioration that comes with millimeter wave spectrum. The spatially confined nature of these beams makes millimeter wave links resilient to eavesdropping and jamming attacks. However, the millimeter wave radios find each other and establish communication by searching every possible angular direction, which increases the potential for the millimeter wave radios to be attacked. In this thesis, we showcase a secure method of establishing this communication link that avoids looking in the direction of a potential attacker. We then employ an artificial intelligence capable of controlling this search by sweeping a subset of all possible directions in the millimeter wave transmitter codebook based on a proposed metric that quantifies the secrecy of communication. We evaluate our proposed system through numerical simulations and an experimental real-life implementation on the CCI xG Testbed.