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Efficient Password Mechanism to Overcome Spyware Attack: Quantum Network and AI
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Author(s): Ajith Peter Vianney R. (Sathyabama Institute of Science and Technology, India), S. Manikandan (Sathyabama Institute of Science and Technology, India)and A. C. Santha Sheela (Sathyabama Institute of Science and Technology, India)
Copyright: 2025
Pages: 14
Source title:
Multidisciplinary Applications of AI and Quantum Networking
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)and Jose Anand (KCG College of Technology, India)
DOI: 10.4018/979-8-3693-9336-9.ch005
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Abstract
This study enhances existing authentication systems that use one-time passwords (OTP) and personal identification numbers (PIN) by adding biometric data as a second layer of user authentication. As an alternative to entering the password as normal, users using the recommended method doodle each digit on the touchscreen of the device. The authors conduct a comprehensive evaluation of each handwritten digit's robustness and discriminative ability, along with an assessment of the proposed biometric technique's performance with longer passwords. The e-BioDigit database, comprising handwritten digits 0 through 9, is created using finger input on a mobile device. In summary, the implementation of the suggested technique aimed at enhancing the security of existing PIN and OTP systems has yielded positive outcomes. Specifically, in scenarios where the attacker is already aware of the password, the method demonstrates equal error rates of approximately 4.0%. This stands in stark contrast to traditional PIN and OTP systems, where an impersonation attack would invariably succeed in 100% of cases.
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