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Facial captures are widely used in many access control applications to authenticate individuals, and grant access to protected information and locations. For instance, in passport or smart card applications, many facial images must be secured during the enrollment process, prior to exchange and storage. Digital watermarking may be used to assure integrity and authenticity of these facial images against unauthorized manipulations, through fragile and robust water marking, respectively. It can also combine other biometric traits to be embedded as invisible watermarks in these facial captures to improve individual verification. Evolutionary Computation (EC) techniques have been proposed to optimize watermark embedding parameters in Intelligent Watermarking (IW) literature. The goal of such optimization problem is to find the trade-off between conflicting objectives of watermark quality and robustness. Securing streams of high-resolution biometric facial captures results in a large number of optimization problems of high dimension search space.