A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments

The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims to demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research.

Identification and Security Implications of Biometrics

The usage of biometrics has become more frequent over the past couple of decades, notably due to technological advancements. Evolving technology in the field of biometrics has also led to increased accuracy of associated software, which have provided the opportunity to use a multitude of different human characteristics for identification and/or verification purposes. The current study assessed the usage of biometrics in casinos, hospitals, and law enforcement agencies using a survey methodology. Results indicated that privacy concerns related to the use of biometrics may not be as prevalent as indicated in the literature. Additionally, results indicated that the utilization of biometrics has led to increased accuracy in identification and verification processes, led to enhanced security, and would be highly recommended to other institutions. Information obtained from the literature notes the racial bias in facial recognition technologies due to algorithmic development based solely upon features of Caucasian individuals. Efforts need to be made to create facial recognition algorithms that are more racially and ethnically diverse

Multibiometric security in wireless communication systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition. First is the enrolment phase by which the database of watermarked fingerprints with memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel. Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present one’s fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user. The following three steps then involve speaker recognition including the user responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user. In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and sliding neighborhood) have been followed with further two steps for embedding, and extracting the watermark into the enhanced fingerprint image utilising Discrete Wavelet Transform (DWT). In the speaker recognition stage, the limitations of this technique in wireless communication have been addressed by sending voice feature (cepstral coefficients) instead of raw sample. This scheme is to reap the advantages of reducing the transmission time and dependency of the data on communication channel, together with no loss of packet. Finally, the obtained results have verified the claims

Evaluation and Understandability of Face Image Quality Assessment

Face image quality assessment (FIQA) has been an area of interest to researchers as a way to improve the face recognition accuracy. By filtering out the low quality images we can reduce various difficulties faced in unconstrained face recognition, such as, failure in face or facial landmark detection or low presence of useful facial information. In last decade or so, researchers have proposed different methods to assess the face image quality, spanning from fusion of quality measures to using learning based methods. Different approaches have their own strength and weaknesses. But, it is hard to perform a comparative assessment of these methods without a database containing wide variety of face quality, a suitable training protocol that can efficiently utilize this large-scale dataset. In this thesis we focus on developing an evaluation platfrom using a large scale face database containing wide ranging face image quality and try to deconstruct the reason behind the predicted scores of learning based face image quality assessment methods. Contributions of this thesis is two-fold. Firstly, (i) a carefully crafted large scale database dedicated entirely to face image quality assessment has been proposed; (ii) a learning to rank based large-scale training protocol is devel- oped. Finally, (iii) a comprehensive study of 15 face image quality assessment methods using 12 different feature types, and relative ranking based label generation schemes, is performed. Evalua- tion results show various insights about the assessment methods which indicate the significance of the proposed database and the training protocol. Secondly, we have seen that in last few years, researchers have tried various learning based approaches to assess the face image quality. Most of these methods offer either a quality bin or a score summary as a measure of the biometric quality of the face image. But, to the best of our knowledge, so far there has not been any investigation on what are the explainable reasons behind the predicted scores. In this thesis, we propose a method to provide a clear and concise understanding of the predicted quality score of a learning based face image quality assessment. It is believed that this approach can be integrated into the FBI’s understandable template and can help in improving the image acquisition process by providing information on what quality factors need to be addressed

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book