Face recognition system is the most widely used application in the field of security and especially in border control. This system may be exposed to direct or indirect attacks through the use of face morphing attacks (FMAs). Face morphing attacks is the process of producing a passport photo resulting from a mixture of two images, one of which is for an ordinary person and the other is a judicially required. In this case, a face recognition system may allow travel of  persons not permitted to travel through face morphing image in a Machine-Readable Electronic Travel Document (eMRTD) or electronic passport at Automatic Border Control (ABC) gates. In creating an electronic passport, most countries rely on applicant to submit images in a form of a document or via the Internet, and this allows applicants to manipulate the images to produce morphing images. These photos allow both beneficial and harmful partners to cross borders using the same passport. This is considered a major threat to the security systems that allow them to travel without revealing their true identity. This paper aims to provide a comprehensive overview of face morphing attacks and the development taking place in this specialty. This paper describes the techniques for generating metamorphic images and challenges they face, in addition to the advantages and disadvantages of these techniques. It also dealt with types of techniques used in detecting and determining the attack of mutant faces in the field of deep learning or machine learning, in addition to the laws and criteria for measuring the efficiency of the algorithms used. It provides a general summary of the work that has been produced in this field.

Biometric forms major and very effective role nowadays in many fields such as health, reliability, devices, phones, banking, airport security, and others because of its unique characteristics for each person that cannot be replicated in another person. Therefore, most security systems rely and verify biometric properties. Airport security systems rely directly on facial recognition, but these systems may be exposed to attacks by the use of morphing faces in the passport image that allows multiple users to use the same passport. This paper presents a complete system consist of three stage, the first stage generating morphing faces based on edge detection to determine landmark and combine between landmarks to produce morphing. The second stage passing images on to the face recognition system that using Local Binary Pattern to features extraction, the final stage how to detect image bona fide or morph using texture techniques represented by each Local binary pattern and Gray-Level Co-Occurrence Matrix. With the use of the Wasserstein Distance measure, which has not previously been used in this field. The method gave effective results showing the mechanism of reducing morphing attack.

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