The integration of biometrics in modern security has become like a massive boost for information security. The process of recognition has become useful to security as there are various elements of recognition that biometrics use to match the live template and the stored template to give the desired return (Metheny 2013, p.71-102). Various features utilized in the biometrics are often extracted from the biometric modalities that come from the stored data about them. The degree of similarity is the found using when the data from the templates are properly authenticated.
Biometric recognition methods
Fingerprint recognition-It is considered as one of the oldest techniques of biometric recognition. It exploits the uniqueness of furrows and ridges to match data for authentication. Finger recognition is an efficient method but possesses certain shortcomings that can make be an obstacle to its performance. Scars and cuts can confuse the system and impede the performance. It is easier to match since it has small template size (John 2009, p.129-152). It offers quick and high performance.
Face recognition-it uses the facial metric and Eigen faces to enhance recognition where facial attributes and skin texture are analyzed to match the stored data. It is always easy to save the templates of the facial elements. Face recognition is one of the socially accepted techniques with good performance. However, look alike can make it seem vulnerable.
DNA recognition-it uses the genetic materials found in the body cells. The use of collected DNA samples which are in turn fragmented to give shorter pieces used for comparison. The fragments are often compared with the stored samples to provide similar matching so that authentication can be guaranteed (Tari 2014, p.54-57). It is considered one of the highly unique techniques to provide the required similarity for sensitive security issues. It is also a very high-performance technique that can hardly be compromised. Due to its high performance, it requires too much information that infringes the privacy of those involved in the process.
Voice recognition methods
Voice recognition is one of the biometric techniques used to identify individual elements in the information technology. It uses varied techniques to bring out the similarity between the stored voice sample and the actual data. The methods are as follows. Its primary focus is always on the features that provide speech rather than sound and pronunciation. It analyzes the vocal properties such as the vocal track, nasal cavities, mouth, etc (Pearson 2012, p.3-42). it also considers other mechanisms for processing the speech in the human body are all brought into perspective. Once the right vocal property is analyzed, it is matched with stored templates that are used to determine the similarities of the data for authentication. The voice recognition methods are as follows;
Text-dependent systems-under this method, user records a phrase or word with the system. During the recognition process, he/she is required to speak the earlier recorded word for matching with the pattern that had been stored. It is considered an easy to use a technique that is also inexpensive (Arasaratnam 2011, p.1-13).
Text-prompted systems-in this method, the system displays the vocabulary that had been stored for the user to read or repeat. The method allows for comparison, and if the texts and vocabularies are similar, then the user is granted access to the system. It is not a high-performance method compared to text-dependent systems (Arasaratnam 2011, p.1-13).
Text-independent systems-the method incorporates the lack of prior knowledge of the vocabulary. The systems generate the reference templates varied phonetics for different voices that are used to recognize the individual. It is a very high-performance technique that is uniquely designed to beat fraudulent intent (Arasaratnam 2011, p.1-13).
Bibliography
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Tari, Z. (2014). Security and Privacy in Cloud Computing. IEEE Cloud Comput. IEEE
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