Facial Image Encryption for Secure Face Recognition System

Abstract

A biometric authentication system is more convenient and secure than graphical or textual passwords when accessing information systems. Unfortunately, biometric authentication systems have the disadvantage of being susceptible to spoofing attacks. Authentication schemes based on biometrics, including face recognition, are susceptible to spoofing. This paper proposes an image encryption scheme to counter spoofing attacks by integrating it into the pipeline of Linear Discriminant Analysis (LDA) based face recognition. The encryption scheme uses XOR pixels substitution and cellular automata for scrambling. A single key is used to encrypt the training and testing datasets in LDA face recognition system. For added security, the encryption step requires input images of faces to be encrypted with the correct key before the system can recognize the images. An LDA face recognition scheme based on random forest classifiers has achieved 96.25% accuracy on ORL dataset in classifying encrypted test face images. In a test where original test face images were not encrypted with keys used for encrypted feature databases, the system achieved 8.75% accuracy only showing it is capable of resisting spoofing attacks.

Confusion and Diffusion Techniques for Image Encryption Process Based on Chaos System

“…Previous research performed face recognition with an image encryption scheme using XOR operations and pixel permutation with a randomization method. In addition, this research used LDA for the facial recognition algorithm [8]. This research showed that the proposed system only achieved an accuracy of 8.75%.…”

Encryption algorithm based on fractional order chaotic system combined with adaptive predefined time synchronization

“…Moreover, the signal is extremely sensitive to the change of system parameters and the disturbance of initial conditions [9]; [10]. Thus, chaotic systems provide a less consumption and higher speed means of implementing encryption tasks for large-scale data such as images [16]; [17]; [18], video and audio [11]; [19]. In order to combine chaotic systems with encryption algorithms, many properties of chaotic systems have been studied and developed [20]; [21]; [22]; [23]; [24]; [25]; [26].…”