Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Biometrics offers greater security and convenience than traditional methods of personal recognition. In some applications, biometrics can replace or supplement the existing technology. In others, it is the only viable approach. But how secure is biometrics? And what are the privacy implications?. <s> BIB001 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or, simply, biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics, it is possible to confirm or establish an individual's identity based on "who she is", rather than by "what she possesses" (e.g., an ID card) or "what she remembers" (e.g., a password). We give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns. <s> BIB002 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Biometrics is a rapidly evolving field with applications ranging from accessing ones computer to gaining entry into a country. The deployment of large-scale biometric systems in both commercial and government applications has increased public awareness of this technology. Recent years have seen significant growth in biometric research resulting in the development of innovative sensors, new algorithms, enhanced test methodologies and novel applications. This book addresses this void by inviting some of the prominent researchers in Biometrics to contribute chapters describing the fundamentals as well as the latest innovations in their respective areas of expertise. <s> BIB003 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Cattle identification receives a great research attention as a dominant way to maintain the livestock. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification approach from live captured muzzle print images with local invariant features. The presented approach compensates some weakness of traditional cattle identification schemes in terms of accuracy and processing time. The proposed scheme uses Scale Invariant Feature Transform (SIFT) for detecting the interesting points for image matching. In order to enhance the robustness of the presented technique, a Random Sample Consensus (RANSAC) algorithm has been coupled with the SIFT output to remove the outlier points and achieve more robustness. The experimental evaluations prove the superiority of the presented approach because it achieves 93.3% identification accuracy in reasonable processing time compared to 90% identification accuracy achieved by some other reported approaches. <s> BIB004 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Recently, forensic science has had many challenges in many different types of crimes and crime scenes, vary from physical crimes to cyber or computer crimes. Accurate and efficient human identification or recognition have become crucial for forensic applications due to the large diversity of crime scenes, and because of the increasing need to accurately identify criminals from the available crime evidences. Biometrics is an emerging technology that provides accurate and highly secure personal identification and verification systems for civilian and forensic applications. The positive impact of biometric modalities on forensic science began with the rapid developments in computer science, computational intelligence, and computing approaches. These advancements have been reflected in the biometric modality capturing process, feature extraction, feature robustness, and features matching. A complete and automatic biometric identification or recognition systems have been built accordingly. This chapter presents a study of the impacts of using some biometric modalities in forensic applications. Although biometrics identification replaces human work with computerized and automatic systems in order to achieve better performance, new challenges have arisen. These challenges lie in biometric system reliability and accuracy, system response time, data mining and classification, and protecting user privacy. This chapter sheds light on the positive and the negative impacts of using some biometric modalities in forensic science. In particular, the impacts of fingerprint image, facial image, and iris patterns are considered. The selected modalities are covered preliminarily before tackling their impact on forensic applications. Furthermore, an extensive look at the future of biometric modalities deployment in forensic applications is covered as the last part of the chapter. <s> BIB005 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> We present an electroc1ardiogram (ECG)-based data encryption (EDE) scheme for implantable medical devices (IMDs). IMDs, including pacemakers and cardiac defibrillators, perform therapeutic or even life-saving functions and store sensitive data; therefore, it is important to prevent adversaries from having access to them. The EDE is designed with the ability to provide information-theoretically unbreakable encryption where two well-known techniques of classic one-time pads (OTPs) and error correcting codes are combined to achieve a cryptographic primitive for IMDs. Unlike other ECG-based key agreement schemes where ECG features are used to facilitate a key distribution, in the EDE scheme, random binary strings generated from ECG signals are directly used as keys for encryption. OTP keys are generated by the IMD and the programmer, respectively, before each encryption attempt; thus, the EDE does not require a cryptographic infrastructure to support a key distribution, storage, revocation, and refreshment. Protected by the EDE, IMDs could not be accessed by adversaries; however, medical personnel can have access to them by measuring real-time ECG data in emergencies. Therefore, the EDE design achieves a balance of high security and high accessibility for the IMD. Our data and security analysis shows that the EDE is a viable scheme for protecting IMDs. <s> BIB006 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Implantable medical devices (IMDs) are normally used for monitoring and treating various medical conditions. These days, wireless modules have become an intrinsic part of many modern IMDs. So, doctors can use device programmers wirelessly to configure parameters in the IMDs. However, such a wireless technology exposes the IMDs to security attacks. In this paper, we analyze potential threats faced by the IMDs and discuss security solutions proposed in the existing literature to counter these threats. Securing an IMD involves three design tradeoffs that require a careful consideration. The first one is security versus accessibility in an emergency situation. We compare the IMD security schemes in the literature in terms of their merits and disadvantages. The second one is the tradeoff between the security schemes for supporting emergency access and those for supporting normal check-up access to the IMDs. This normal check-up access to the IMDs should avoid extra resource consumptions, which is different from the requirement in the emergency access. The third one is between the requirements of strong security and limited resources. The IMD, as a tiny wireless device used for medical purposes, has very limited resources when compared with a generic wireless sensor device/node. We analyze various schemes that aim to conserve the underlying resources of an IMD and also counter battery denial of service attacks from different perspectives. Based on the literature review, we analyze general concerns in the IMD security design from the system engineering point of view, and discuss possible future research directions. <s> BIB007 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Introduction <s> Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of $N$ bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system. <s> BIB008
Biometrics is a technology that uses the unique patterns of physical or behavioral traits of users for authentication or identification. With biometric scanners on smartphones and other devices becoming more prevalent, as well as a growing number of services calling for high security and good customer experience, traditional methods of authentication (e.g., passwords and PINs) are increasingly being replaced by biometric technology BIB003 . Passwords have some obvious drawbacks-they could be stolen, lost, or forgotten. In contrast, biometrics offer an alternative solution to the task of personal authentication or identification based on biometric traits. To be forgotten or lost is impossible, and unlike passwords, they are hard to forge. There are some biometric traits that can be defined for an individual; for example, fingerprint, finger-vein, iris, voice, face, and so on  . Generally, a typical biometric system comprises four modules, namely, sensor module, feature extraction module, template database, and matching module. Specifically, the sensor module acquires the biometric image. A set of global or local features are extracted from the acquired biometric image by the feature extraction module. Structured feature representations are stored in the template database as template data. The matching module is responsible for comparing the query and template data to reach a match or non-match verdict. A typical biometric system carries out authentication in two stages BIB001 BIB005 -the enrollment stage and verification stage-as shown in Figure 1 . Take fingerprint recognition as an example. In the stage of enrollment, a user presents their finger to the fingerprint sensor and a fingerprint image is acquired by the sensor module. Certain features of the acquired fingerprint image are extracted, and further adapted or transformed to generate template data for the purpose of comparison in the verification stage. In the verification stage, the fingerprint image of a query is collected by the sensor module. The feature representations of the query fingerprint image go through the same process as in the enrollment stage, so as to obtain query data. The query data are then compared with the template data so that a matching outcome is attained. of the acquired fingerprint image are extracted, and further adapted or transformed to generate template data for the purpose of comparison in the verification stage. In the verification stage, the fingerprint image of a query is collected by the sensor module. The feature representations of the query fingerprint image go through the same process as in the enrollment stage, so as to obtain query data. The query data are then compared with the template data so that a matching outcome is attained. Due to some specific properties possessed by biometrics, biometric systems have been adopted in many civilian and military applications BIB007 BIB008 BIB006 BIB004 in the areas of law enforcement, border control, consumer or residential biometrics, and financial services. (1) Law enforcement: Biometric technology has been embraced with open arms by law enforcement agencies across the world for its efficiency in security-oriented scenarios. In fact, biometrics is not a new tool in law enforcement. Fingerprint biometrics have been adopted by Argentinian criminologists for more than a century. Nowadays, with rapid technological development, biometrics have launched a worldwide revolution in law enforcement. Biometric recognition systems have now been utilized by law enforcement agencies of many countries, including the United States, United Kingdom, Australia, and China. For example, in 2011, the Department of Defense and the FBI started working on the United States' next generation biometric system, named Next Generation Identification (NGI), which is designed to include fingerprint, face, iris, and palm data, and their facial recognition program became fully operational in late 2014  . (2) Border control: In order to prevent identity fraud and strengthen border and national security, many countries employ biometric systems to track and manage the flow of passengers across borders. For instance, since 2008, all non-Americans who travel to the United States are requested to scan their fingerprint by US border security officials  . In order to eliminate the need for paper passports, Australia is planning to boost its "Seamless Traveler" program. The proposal of this program is to have 90 percent of the 35 million annual travelers to enter Australia via a paperless biometric recognition system by 2020 [11] . Due to some specific properties possessed by biometrics, biometric systems have been adopted in many civilian and military applications BIB007 BIB008 BIB006 BIB004 in the areas of law enforcement, border control, consumer or residential biometrics, and financial services. (1) Law enforcement: Biometric technology has been embraced with open arms by law enforcement agencies across the world for its efficiency in security-oriented scenarios. In fact, biometrics is not a new tool in law enforcement. Fingerprint biometrics have been adopted by Argentinian criminologists for more than a century. Nowadays, with rapid technological development, biometrics have launched a worldwide revolution in law enforcement. Biometric recognition systems have now been utilized by law enforcement agencies of many countries, including the United States, United Kingdom, Australia, and China. For example, in 2011, the Department of Defense and the FBI started working on the United States' next generation biometric system, named Next Generation Identification (NGI), which is designed to include fingerprint, face, iris, and palm data, and their facial recognition program became fully operational in late 2014  . (2) Border control: In order to prevent identity fraud and strengthen border and national security, many countries employ biometric systems to track and manage the flow of passengers across borders. For instance, since 2008, all non-Americans who travel to the United States are requested to scan their fingerprint by US border security officials  . In order to eliminate the need for paper passports, Australia is planning to boost its "Seamless Traveler" program. The proposal of this program is to have 90 percent of the 35 million annual travelers to enter Australia via a paperless biometric recognition system by 2020 [11] . (3) Consumer biometrics: Consumer devices equipped with biometric systems are standalone products for the consumer market, such as door locks, surveillance systems, automotive, and especially mobile devices (smartphones, tablets, etc.). In the past, passwords were the only secure way of authentication, and fingerprint scanners were most likely used by law enforcement agencies and the military. However, times have changed. In the last decade, biometric technology has developed in leaps and bounds and spread to every corner of our lives as a more secure method of authentication. With the popularity of smart phones, mobile phones utilizing biometrics is a winning combination in the consumer market, allowing biometric technology to become much more widely accepted [12] . (4) Financial services: Finance is the most mature biometrics market outside the domain of law enforcement for the logic that protecting money is the first priority for most people. Financial companies have been early adopters of biometrics. For example, cash machines with fingerprint readers are currently deployed at an increasing pace [13] . Moreover, a new MasterCard, which includes an embedded fingerprint reader, attempts to introduce a biometric authentication layer for card payment  , so as to enhance customers' comfort level in terms of security and convenience. Compared with other biometric traits (e.g., face, iris, and voice), fingerprint-based recognition systems are studied most extensively and deployed most widely. For a fingerprint, the pattern of valleys and ridges is determined after birth, and different fingerprint patterns are owned by even identical twins BIB003 . It has been reported that the recognition accuracy of fingerprint-based recognition systems is very high  , with the general public showing medium acceptability to fingerprint acquisition BIB002 . This is why fingerprint biometric systems occupy a large market share and have been adopted in various applications. Although fingerprint recognition shows substantial strength and a prosperous future, it has some unsolved issues, such as insufficient accuracy and security concerns. In this paper, a comprehensive review is presented to shed light on the latest development in the study of fingerprint-based biometrics concerning two important aspects-security and recognition accuracy. The main contributions of this paper are highlighted as follows: i. Security and recognition accuracy, despite being two most important aspects in biometric system design, have not been adequately studied simultaneously. Prior to this review paper, no research work has delivered a comprehensive review considering both of them. In this paper, up-to-date research and insights into security and recognition accuracy are thoroughly analyzed and discussed. ii. Based on a thorough analysis, limitations of existing research are discussed and suggestions for future work to overcome those limitations are provided. iii. The two most critical attacks to biometric systems are discussed in this paper. How to resolve the challenges, so as to defend biometric systems, is the focus of current and future biometric security research. iv. Most existing methods, either with or without template protection, were set forth in ideal situations. In this paper, we emphasize the importance of considering recognition accuracy under non-ideal conditions. Our analysis is backed by solid evidence and detailed comparison. The rest of this paper is organized as follows. In Section 2, the security of biometrics is thoroughly analyzed from the perspective of attack points and countermeasures. In Section 3, system recognition accuracy under different conditions is discussed. The conclusion and future work is given in Section 4.