Union Carbide Case Analysis

In modern society, the ability of reliably identify individual information is a fundamental requirement in different area，especially in forensics, public security and computer security. In a few decades of development, biometric technology has made a great progress (e.g. finger printing, Face-recognition technology, Iris scanning) and its system is becoming common. Although their use provide important advantages in government agencies, businesses and personal identification, the widespread use of biometric technologies also cause adverse consequences. This paper focuses on the above key issues in biometric technologies.The main contributions of this paper are summarized as follows: Firstly, give a special definition and operation principle of biometric technologies through the biometric user's perspective; Secondly, discuss different types of commonly biometrics technology and compare advantages and disadvantages; Finally, find the future development trend of biometric technologies.

Biometric technologies, usually through the computer， collect the human's biological characteristics and then convert them into a specific data to identify and distinguish different people. Biological tracts have been used for authentication purposes include fingerprints, face, palm, hand vein pattern, tooth, iris, ear shapes and DNA（Langenderfer et al，2005）

, while the sound, personal signature, body shape and walking posture have been used as behavioral measures (Chen et al, 2016). A typical biometric system has two stages of operation, namely, the enrollment stage and the recognition stage (Jain et al,2016). At the enrollment stage, biometric systems obtain special biometric information from the individual, collect and organize the data into the bioinformatics database. During the recognition stage, the identification system retrieves the biometric characteristics of the individual again and extracts the feature set from the database into the template to determine the matching or authenticity of the claimed identity. The latter function is often referred to as identification, and the results of the recognition operation are divided into two cases: (i) querying one or more user identities through a biological sample, or (ii) the biological sample and the database do not match. If the biometric system is forced to output identity, it is called a closed sign. On the other hand, the choice of refusal to respond leads to an open recognition system (Jain et al,2016).

According to the requirement levels of safety performance, different types of biometric technologies have been widely used in the social life, especially the Fingerprint scanning. Fingerprint scanning is one of the cheapest, productive and accurate biometric applications. It uses different materials to extract biometric features for register and compare such as silicon, optics, thermal or ultrasonic systems（Langenderfer et al，2005）. Most of the current fingerprint scanners are based on a specific camera for fingerprint scanning of the optical system, but due to the smaller size and cost, the updated system is often silicon. Fingerprint scanners are now included many features, such as proofing of identity information (Oloyede & Hancke 2016), verifying employee attendance, identity authentication at entry and exit, even as identity verification at the Disney World. Although the use of fingerprint identification technology widely, it does constitute some unique privacy issues. First of all，the fingerprint has already become a legitimate identification criteria, however, non-law enforcement entities can also use this technology to steal personal information data to carry out fraud or crime. Secondly, because the fingerprint is different from other technologies that do not need to personally confirm, it can also be obtained through other means, which greatly reduces the fingerprint identification technology security performance.

Face-recognition technology has been another interesting topic of researchers in biometric technology, because face is the most natural and critical biological characteristics of the human body. Although the human face is the most natural biometric feature, human face contains massive information and difficult to statistics, therefore, research institutions have invested a lot of time to develop a powerful automatic Face-recognition system. The face recognition is divided into two modes: 2D features and 3D features (Unar,2014). Scientists think that the 3D face-recognition becomes a new trend and proposed to basic problems associated with 2D face-recognition such as image degradation, poor alignment and movement of head and facial expressions. 3D face-recognition technology has higher accuracy in facial images obtained under visible light. However, a person's face may change over time or cosmetic and cosmetic surgery, which may have a significant impact on the accuracy of face-recognition systems. they are very much prone to recognition errors (Unar,2014). Another factor limiting the use of this system is expensive imaging hardware because of higher requirements of the sensors and imaging hardware.