Software and hardware requirements of steganography techniques applied over the protection of biometric data
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Identification of persons by way of biometric features is an emerging phenomenon. Over the years, biometric recognition has received much attention due to its need for security. Amongst the many existing biometrics, fingerprints are considered to be one of the most practical ones. Techniques such as watermarking and steganography have been used in attempt to improve security of biometric data. Watermarking is the process of embedding information into a carrier file for the protection of ownership/copyright of music, video or image files, whilst steganography is the art of hiding information. This paper presents an overview of steganography techniques applied in the protection of biometric data in fingerprints. It is novel in that we also discuss the strengths and weaknesses of targeted and blind steganalysis strategies for breaking steganography techniques.
Biometric systems allow for convenient identification to take place based on a person’s physical or behavioural characteristics. In comparison with conventional token-based or knowledge based systems, they link identities directly to the owners. Moreover, these identities cannot be given up or lost easily. The uses of biometric procedures have evolved rapidly in the past decade and are used in many different areas, such as banking and government agencies, retail sales, law enforcement, health services, and airport/border controls [3]. In recent years, companies such as Apple and Samsung has integrated biometrics into their latest mobile devices, which can now be unlocked with the owner’s fingerprint data [43, 64]. One of the main reasons that these biometric mechanisms are gaining popularity is because of their ability to distinguish between an authorized user and a deceptive one [52. At present, fingerprint biometrics are said to be the most common mechanism, as these are convenient to use, and less expensive to maintain in comparison to other systems. However, as the development of these applications continues to expand, the matter of security and confidentiality cannot be ignored. The security and integrity of biometric data presents a major challenge, as many benefits of biometrics may quite easily become impediment. Thus, from the point of view of promoting the extensive usage of biometric techniques, the necessity of safeguarding biometric data, in particular fingerprint data becomes crucial [37]. For example, fingerprint biometric systems contain sensitive information such as minutia points (explained in the next section) which is used to uniquely identify each fingerprint. The use of latent fingerprints is one way that an unauthorized user can access a system. A latent fingerprint can be easily collected as people leave latent prints when they touch hard surfaces. If an unauthorized user was successful in retrieving a latent print it may enable him/her to gain access to the system hence potentially endanger the privacy of users. Additionally, stolen data may be used for illegal purposes, such as identity theft, forgery or fraud. Therefore, increased security of the data is critical [51].
There are procedures in existence that can help to optimize the security of biometric data, one being, information hiding. Information hiding techniques like watermarking and steganography can add to the security of biometric systems. Watermarking can be explained as a process of embedding information into a carrier file in order to secure copyright, typically ownership [58]. Watermarks can be either visible or nonvisible to the human eye. Steganography is the process of hiding critical data (i.e. identity pin) in a trusted carrier medium (i.e. digital fingerprint image) without third parties sharing any awareness that the information exists. Both methods of information hiding are closely connected [24]. Steganography can be applied using the following two approaches: reversible and irreversible [100]. A reversible data hiding technique, allows for a full recovery of the original carrier file even after extraction of the hidden data. Whereas, an irreversible technique may leave the original carrier file distorted after the hidden data is extracted [88]. Over the past number of years, many image-based steganography methods have been broadly classified depending upon the domain as spatial domain steganography and frequency domain steganography. In Spatial domain steganography, methods such as correlation based techniques, pixel value differencing and LSB substitution, which will be explained later, have been developed and tested. Frequency domain steganography methods consist of many different domains, such as Discrete Cosine Transform (DCT) domain, Discrete Fourier Transform (DFT) domain, Discrete Wavelet Transform (DWT) domain, Singular Value Decomposition (SVD). Frequency domain methods are considered to be more robust than that of spatial domain methods [46, 58, 93, 99].