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This paper proposed a noble face recognition and biometric encryption technique for the biometric passport by applying encrypted biometric data encoded into the High-Capacity Color Two-Dimensional (HCC2D) Code to secure the biometric data. The proposed biometric encryption method is attained by applying the Secure Force (SF) algorithm and encoding it into the HCC2D code. The face recognition technology is achieved by combining the Viola-Jones (VJ) algorithm and the Local Binary Patterns (LBP) algorithm to extract the facial features and generate the template. This method will ensure the safety and security of a biometric passport from unauthorized access without knowing the passport holder. The proposed method will provide more security for border crossing and illegal immigrants for national security. [ABSTRACT FROM AUTHOR]

Embracing Artificial Intelligence (AI) is becoming more common in a variety of areas, including healthcare, banking, and transportation, and it is based on substantial data analysis. However, utilizing data for AI raises a number of obstacles. This extensive article examines the challenges connected with using data for AI, including data quality, volume, privacy and security, bias and fairness, interpretability and ethical considerations, and the required technical knowledge. The investigation delves into each obstacle, providing insightful solutions for businesses and organizations to properly handle these complexities. Organizations may effectively harness AI's capabilities to make educated decisions by understanding and proactively tackling these difficulties, obtaining a competitive edge in the digital era. This review study, which provides a thorough examination of numerous solutions developed over the last decade to address data difficulties for AI, is expected to be a helpful resource for the scientific research community. It not only provides insights into current difficulties, but it also serves as a platform for creating novel ideas to alter our approaches to data strategies for AI. [ABSTRACT FROM AUTHOR]

A biometric passport includes demographic information and biometric details. It contains some applications that are currently and probable concerning national security such as frontier protection, illegal immigration, criminals, terrorists, and fake passport. Over the fifteen years, most of the countries have adopted biometric-passports based on International Civil Aviation Organization (ICAO) and Machine Readable Travel Documents (MRTD) standardization. However, the Radio Frequency Identification (RFID) system contains a threat scenario that exists in privacy violation issues such as identity theft, data leakage threats, host listing, and tracking. To overcome these issues, this paper proposed a face recognition based on facial blemishes detection and encrypted into the High Capacity Color 2-Dimensional (HCC2D) code for biometric passport security. This includes facial blemishes features detection to generate the template and encrypted by applying the Secure Force (SF) algorithm to secure biometric information. Facial blemishes are detected by applying the Active Appearance Model (AAM) using Principle Component Analysis (PCA) and Canny edge detector with Speeded Up Robust Features (SURF) detection algorithm. The proposed technique attained a 93.06% accuracy level for the dataset Indian Institute of Technology Kanpur (IITK). This technique will enhance biometric passport security to protect the biometric information from an intruder. [ABSTRACT FROM AUTHOR]

An e-passport contains the personal and biometric information of a person. It has some current and possible applications relating to national security and law enforcement such as border security, illegal immigration, terrorism, criminals, fake passport, and so on. In the past decade, a number of countries have implemented the e-passport based on Machine Readable Travel Documents (MRTD) and International Civil Aviation Organization (ICAO) standardization. However, there is a threat scenario in the privacy infringement problem due to Radio Frequency Identification Device (RFID) such as data leakage threats, identity theft, tracking, and host listing. In this article, a multimodal biometric, secure encrypted data and encrypted biometric encoded in the Quick Response Code (QR code) based e-passport authentication method is proposed for national security application. Further, Personal information and biometric data are encrypted by applying the Advanced Encryption Standard (AES) and the Secure Hash Algorithm (SHA) 256 algorithm. More specifically, face recognition based on facial marks size detection and hand geometry detection is used for a biometric passport to enhance and secure the authentication level. The proposed method achieved an accuracy level of 92% for IITK (Indian Institute of Technology, Kanpur) dataset, an accuracy level of 93% for FEI (Fundação Educacional Inaciana) dataset in mark size detection and an accuracy level of 96.67% achieved in the hand geometry detection. [ABSTRACT FROM AUTHOR]