Biblio

The fast advancement in the last two decades proposed a new challenge in security. In addition, the methods used to secure information are drawing more attention and under intense investigation by researchers around the globe. However, securing data is a very hard task, due to the escalation of threat levels. Several technologies and techniques developed and used to secure data throughout communication or by direct access to the information as an example encryption techniques and authentication techniques. A most recent development methods used to enhance security is by using human biometric characteristics such as thumb, hand, eye, cornea, and DNA; to enforce the security of a system toward higher level, human DNA is a promising field and human biometric characteristics can enhance the security of any system using biometric features for authentication. Furthermore, the proposed methods does not fulfil or present the ultimate solution toward tightening the system security. However, one of the proposed solutions enroll a technique to encrypt the biometric characteristic using a well-known cryptosystem technique. In this paper, an overview presented on the benefits of incorporating a human DNA based security systems and the overall effect on how such systems enhance the security of a system. In addition, an algorithm is proposed for practical application and the implementation discussed briefly.

Remote authentication via biometric features has received much attention recently, hence the security of biometric data is of great importance. Here a crypto-steganography method applied for the protection of biometric data is implemented. It include semantic segmentation, chaotic encryption, data hiding and fingerprint recognition to avoid the risk of spoofing attacks. Semantically segmented image of the person to be authenticated is used as the cover image and chaotic encrypted fingerprint image is used as secret image here. Chaotic encrypted fingerprint image is embedded into the cover image using Integer Wavelet Transform (IWT). Extracted fingerprint image is then compared with the fingerprints in database to authenticate the person. Qualified Significant Wavelet Trees (QSWT`s) of the cover image act as the target coefficients to insert the secret image. IWT provide both invisibility and resistance against the lossy transmissions. Experimental result shows that the semantic segmentation reduces the bandwidth efficiently. In addition, chaotic encryption and IWT based data hiding increases the security of the transmitted biometric data.

Sophisticated technologies realized from applying the idea of biometric identification are increasingly applied in the entrance security management system, private document protection, and security access control. Common biometric identification involves voice, attitude, keystroke, signature, iris, face, palm or finger prints, etc. Still, there are novel identification technologies based on the individual's biometric features under development [1-4].