Eye Blink Password Based Secure Authentication System

Conventional authentication mechanisms such as alphanumeric passwords, PIN codes, and even biometric identifiers like fingerprints and facial recognition suffer from critical drawbacks including vulnerability to theft, shoulder surfing, thermal residue attacks, and hygiene concerns in shared environments. To overcome these limitations, eye-based authentication techniques have emerged as a viable alternative by exploiting the uniqueness of ocular characteristics and dynamic blink sequences. This survey explores recent developments in secure authentication systems that utilize eye blinks as password inputs. It reviews approaches employing computer vision techniques such as Haar Cascade classifiers, Histogram of Oriented Gradients (HOG), and Eye Aspect Ratio (EAR) computations for real-time blink recognition. Furthermore, hybrid models integrating facial recognition, gaze-tracking, and blink-based PIN generation with multi-factor mechanisms like one-time password (OTP) verification are examined. The applications of these systems extend to diverse domains including automated teller machines (ATMs), mobile device access, smart home security, healthcare, and defense sectors, offering a hygienic, contactless, and spoofresistant alternative. The survey also discusses key benefits such as accessibility for differently-abled users, cost-effectiveness, and resistance to shoulder-surfing attacks, while outlining challenges like user fatigue and sensitivity to illumination. By consolidating current methodologies, applications, and limitations, this paper underscores the potential of eye blink passwordbased authentication as a robust, user-friendly, and future-ready replacement for traditional security methods