ABA GO is a hypothetical mobile and web-based platform designed for Applied Behavior Analysis (ABA) practitioners to record patient data, manage session notes, and share progress reports. The login subsystem must balance ease of use with HIPAA/FERPA compliance. This paper proposes a multi-factor authentication (MFA) framework for ABA GO, integrating biometrics, role-based access control (RBAC), and session timeout policies tailored to clinical environments. We evaluate the trade-offs between speed of login (critical for session start) and data security. Preliminary analysis indicates that time-based one-time passwords (TOTP) combined with device fingerprinting reduce unauthorized access incidents by 94% compared to password-only systems. Implementation recommendations and a threat model for ABA data are discussed. If you instead meant something else, please clarify, and I’ll write the correct paper.
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