The widespread use of computers throughout modern society introduces the necessity for usable and counterfeit-resistant authentication methods to ensure secure access to personal resources such as bank accounts, e-mail, and social media. Current authentication methods require tedious memorization of lengthy pass phrases, are often prone to shoulder-surfing, and may be easily replicated (either by counterfeiting parts of the human body or by guessing an authentication token based on readily available information). This paper describes preliminary work toward a counterfeit-resistant usable eye movement-based (CUE) authentication method. CUE does not require any passwords (improving the memorability aspect of the authentication system), and aims to provide high resistance to spoofing and shoulder-surfing by employing the combined biometric capabilities of two behavioral biometric traits: 1) oculomotor plant characteristics (OPC) which represent the internal, non-visible, anatomical structure of the eye; 2) complex eye movement patterns (CEM) which represent the strategies employed by the brain to guide visual attention. Both OPC and CEM are extracted from the eye movement signal provided by an eye tracking system. Preliminary results indicate that the fusion of OPC and CEM traits is capable of providing a 30% reduction in authentication error when compared to the authentication accuracy of individual traits.