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- Information Systems Dissertation Topic with Titles
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Biometrics have been predicted as being “one of the top ten emerging technologies that will change the world” (Woodward et al., 2003, p. xxiii). Biometrics have frequently been represented as technologies with extraordinary powers and various important applications, such as in the areas of defence (Aydoğdu, 2013), authentication (Kanev et al., 2016) and forensic investigations (Jain and Ross, 2015). Their use in national security began to take precedence after the terrorist attacks of September 11, 2001 (Bolle et al., 2013). This research project seeks to take a pragmatic approach to the study of biometrics, evaluating both their advantages and benefits as well as their disadvantages. There are many flaws, for example, in the basic premise of biometrics which will be explored (Pugliese, 2012).
Biometric systems are technologies that scan a subject’s physiological, chemical or other behavioural characteristics in order to verify or authenticate their identity (Pugliese, 2012). This involves a three stage process: first, the biometric imaging system creates an “imprint” of its subject, such as a facial scan - an image of the facial features which records the subject’s unique biometric characteristics (Pugliese, 2012). The facial scan is then converted into a ‘template’ through the use of algorithms. The subject's unique biometric characteristics are then stored for comparison with later scans in which the individual's identity is verified by reference to the initial template (Pugliese, 2012).
Biometrics have a variety of uses; however, the specific emphasis of this research project will be the use of biometrics in forensic investigations. Forensic investigations involve the collection of physical or digital evidence and aim to achieve the reliability, certainty and authority of a scientific enquiry in order to deliver evidence for a legal process upon which a prosecution can be based where a crime has been committed (Turvey and Crowder, 2017). Biometrics thus enable the use of computational techniques to automate and replace earlier manual approaches to forensic examinations. The use of biometrics in the identification of criminal perpetrators is regarded as a fundamental shift in the way that crimes are investigated, with the advantages of improving accuracy, reliability and speed of application in forensic investigations (Saini and Kapoor, 2016).
Research has shown how the science of biometrics has been applied within the field of forensic applications in which effective identification is central to the presentation of evidence. Such techniques can show that a crime has been committed and help in the identification of the criminal (Saini and Kapoor, 2016). Conventional approaches to criminal investigation are time-consuming, resulting in a lot of delay, and often inefficient, leading to high expenditure. There is a need for an automated crime investigation procedure that can provide accurate and reliable methods to detect crime (Saini and Kapoor, 2016).
Biometrics have been used within the identification process of a suspect through the use of his or her physical characteristics, including their fingerprints, face, hand geometry, iris (physiological), voice and signature (behavioural) (Bolle et al., 2013). Identifiers that are used less frequently or that are still in the early stages of research include DNA, ear shape, odour, retina, skin reflectance, thermogram (physiological), gait, keystroke and lip motion (behavioural) (Bolle et al., 2013). These characteristics are measurable and are unique characteristics that can be used to identify both living and/or deceased individuals (Sauerwein et al., 2017). Biometric systems are made of five integrated modules: sensor module, feature extraction module, matcher module, decision-making module and systems-based module (Arunalatha and Ezhilarasan, 2016).
Biometric technology is regarded as capable of contributing to the detection of crime through associating traces of individuals found at the scene of a crime with identification markers of individuals stored in a database (Saini and Kapoor, 2016). Biometric techniques have also been used post mortem in the identification of unknown individuals. Ever improving digital imaging capabilities have led to more efficient capturing of biometric data, making it more practical to consider data as a part of the biological profile of human remains (Sauerwein et al., 2017).
There are a large number of research studies regarding the variety of techniques used in biometric analyses. Bouchrika et al (2011) have considered the use of gait in forensic biometrics, using the locations of the ankle, knee and hip to drive a measure of matches between walking subjects and image sequences. Their location is determined by reference to the Instantaneous Posture Match algorithm, Harr templates, kinematics and anthropomorphic information, finding that individuals could be identified on CCTV images from the way that they walk or run (Bouchrika et al., 2011). Fingerprints are commonly used for identification; however, the investigation process has typically carried out manually by fingerprint experts. Kärgel et al (2012) find that matching speeds for automatic biometric identification of fingerprints was sufficient, but that error rates were too high for applying the matches in a forensic context (Kärgel et al., 2012).
Benzaoui et al (2014) have also researched the potential for automated personal identification using the shape of the ear, since the ear pattern can provide rich and stable information to differentiate and recognise people. The researchers evaluated the use of various methods including local texture descriptors, local binary patterns, local phase quantization and binarised statistical image features for robust human identification from two-dimensional ear images (Benzaoui et al., 2014). The authors found that local descriptors based on small local image patches are more effective under real-world conditions than the use of global image descriptors (Benzaoui et al., 2014). There is a great deal of research, therefore, that has focused upon specific potential uses of biometrics within forensic investigations. However, each one has shown weaknesses in the techniques, which requires further research.
Biometric systems are also vulnerable to certain types of attack, such as at the sensor level by using fake inputs (Arunalatha and Ezhilarasan, 2016). General mechanisms of computer attacks are also relevant to biometric systems making identification in forensic examinations; spoofing refers to the fraudulent access by an unauthorised person into biometric systems by using fake input to reproduce an authorised person's biometric input (Arunalatha and Ezhilarasan, 2016).
It is clear that while biometrics have shown great potential to be used in forensic investigations, there are also specific weaknesses associated with the particular uses. The gap in the literature that has been identified, therefore, is an overview of the various methods and their applications in forensic sciences which focuses on the advantages and disadvantages of a variety of methods.
Importance of Research
The importance of this research is to understand the contribution that can be made by biometric technologies to the advancement of forensic science in detecting the perpetrators of crimes. As has been discussed, there remain many weaknesses to be addressed in these developing techniques; the research seeks to evaluate the current state of developments of biometric technologies in relation to forensic examinations as well as to consider future potential directions.
Aims and Objectives
The aim of the research is to evaluate the strengths and weaknesses of current trends in biometric science and its application within forensic examinations. In order to further this aim, the following objectives will be pursued:
- To evaluate the current trends in biometrics and possible applications
- To focus specifically on the advantages of biometric methods in forensic investigations
- To evaluate the shortcomings of the various approaches as well as methods to overcome these.
The research study will adopt a qualitative methodology; it aims to evaluate the current trends in biometric technologies through reference to academic journals, conference papers and academic texts. The methodology includes a secondary analysis of existing research studies into biometric methods for identification. The advantage of secondary analysis is that it enables the researcher to spend more time on the analysis and interpretation of data than would be the case using a primary research method (Bryman, 2015). Reference will be made to various journal databases, including ACM Digital Library, IEEE Xplore, SCOPUS, and ProQuest, using search terms such as ‘biometrics’, ‘identification’, ‘authentication’ and ‘forensic investigations’. Searched literature will be limited to the previous 10 years so that only current methods are researched. Due to the limitations of the current project, including word count, it is unlikely that all biometric applications will be fully investigated. However, after a thorough search of the current literature is undertaken, the most relevant studies will be extracted for further investigation.
Chapter 1 will introduce the themes and provide background to the study of biometrics along with an overview of the requirements of forensic examinations.
Chapter 2 will consider the advantages of the use of biometric technologies in forensic examinations, including examining existing methods and how biometrics can improve the automation as well as the accuracy of identification of both suspects and well as victims of crime.
Chapter 3 will evaluate the shortcomings of current biometric techniques in relation to forensic examinations and the problems that need to be overcome in ensuring that such technologies provide reliable evidence upon which prosecutions can be based.
Chapter 4 will provide an overall conclusion to the research question regarding the advantages and disadvantages of biometric technologies in forensic examinations. It will draw conclusions and recommendations as to how the identified difficulties might be overcome and lead to conclusions regarding further avenues of research.
Arunalatha, G., Ezhilarasan, M., (2016). Detecting liveness of fingerprint biometrics. International Journal of Internet Protocol Technology 9, 196-206.
Aydoğdu, U.F., (2013). Technological Dimensions of Defence Against Terrorism. Amsterdam: IOS Press.
Benzaoui, A., Hadid, A., Boukrouche, A., (2014). Ear biometric recognition using local texture descriptors. Journal of Electronic Imaging 23, 5, 053008-1- 053008-12
Bolle, R.M., Connell, J.H., Pankanti, S., Ratha, N.K., Senior, A.W., (2013). Guide to Biometrics. New York. Springer Science & Business Media.
Bouchrika, I., Goffredo, M., Carter, J., Nixon, M., (2011). On Using Gait in Forensic Biometrics. Journal of Forensic Sciences 56, 882–889.
Bryman, A., 2015. Social Research Methods, 5th ed ; Oxford: Oxford University Press.
Jain, A.K., Ross, A., (2015). Bridging the gap: from biometrics to forensics. Philosophical Transactions Royal Society London Biological Sciences 370, 1674
Kanev, K., De Marsico, M., Bottoni, P., Mecca, A., (2016). Mobiles and Wearables: Owner Biometrics and Authentication, in: Proceedings of the International Working Conference on Advanced Visual Interfaces, AVI ’16. ACM, New York, NY, USA,
Kärgel, R., Hildebrandt, M., Dittmann, J., (2012). An Evaluation of Biometric Fingerprint Matchers in a Forensic Context Using Latent Impressions, in: Proceedings of the on Multimedia and Security, MM&Sec ’12. ACM, New York, NY, USA, pp. 133–138.
Pugliese, J., (2012). Biometrics: Bodies, Technologies, Biopolitics. Abingdon: Routledge.
Saini, M., Kapoor, A.K., (2016). Biometrics in Forensic Identification: Applications and Challenges. Journal of Forensic Medicine 1, 1–6.
Sauerwein, K., Saul, T.B., Steadman, D.W., Boehnen, C.B., (2017). The Effect of Decomposition on the Efficacy of Biometrics for Positive Identification. Journal of Forensic Sciences 62, 1599–1602.
Turvey, B.E., Crowder, S., (2017). Forensic Investigations: An Introduction. London: Academic Press.
Woodward, J.D., Orlans, N.M., Higgins, P.T., (2003). Biometrics: Identity Assurance in the Information Age, 1st ed. New York: McGraw-Hill Osborne Media
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