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Biometric access control systems: A review on technologies to improve their efficiency
Abstract
One of the hot topics of today's world is security. Not only companies spend more and more money in order to protect their valuable assets (physical and digital), regular people also need enhanced forms of security regarding personal sensitive information. Traditional password methods for protection of information are prone to brute force attacks, as computational power increases. The focus has then been shifting towards more advanced forms of authentication that do not rely exclusively on a sequence of symbols. The use of biometric authentication has been added as a security feature to numerous systems. Its use has increased in popularity during the last few years, benefiting from a mass implementation of biometric authentication methods in mobile devices (namely laptops and smartphones), such as fingerprint readers and/or built-in cameras. There are already a few available systems which can offer these advantages, but they are typically closed systems that do not integrate well with existing infrastructures. Therefore, this paper intends to review the use of biometric sensors on a fully open and compatible Access Control System.
... Another area where machine learning can be applied to authentication is in the analysis of biometric data [25,39,15]. Biometric authentication methods, such as fingerprint or facial recognition, have become increasingly popular due to their convenience and security. ...
Access control systems are important in regulating who can access physical facilities , computer systems, and data resources. However, traditional access control systems have limitations in adapting to changing user behavior and evolving security threats. We argue that applying machine learning is a promising direction to access control systems can enhance their accuracy, efficiency, and effectiveness. Machine learning can help identify and mitigate security risks in real-time by detecting patterns of suspicious activity that may indicate a security breach or attempted attack. It can also learn to identify anomalies and raise alerts, enabling security personnel to respond quickly and prevent potential security incidents.
... Human identification using biometric technologies has attracted more attention in security applications. Some examples of security applications are access control [2], border control, [3], banking [4], and forensics [5]. Human recognition research projects promise new life to many security-consulting firms and personal identification system manufacturers. ...
Iris recognition as a biometric identification method is one of the most reliable biometric human identification methods. It exploits the distinctive pattern of the iris area. Typically, several steps are performed for iris recognition, namely, pre-processing, segmentation, normalization, extraction, coding and classification. In this article, we present a novel algorithm for iris recognition that includes in addition to iris features extraction and coding the step of feature selection. Furthermore, it enables selecting a variable length of features for iris recognition by adapting our recent algorithm variable length black hole optimization (VLBHO). It is the first variable length feature selection for iris recognition. Our proposed algorithm enables segments-based decomposition of features according to their relevance which makes the optimization more efficient in terms of both memory and computation and more promising in terms of convergence. For classification, the article uses the famous support vector machine (SVM) and the Logistic model. The proposed algorithm has been evaluated based on two iris datasets, namely, IITD and CASIA. The finding is that optimizing feature encoding and selection based on VLBHO is superior to the benchmarks with an improvement percentage of 0.21%.
... In Chen and Zhao (2012), privacy and security of data are analyzed. Concisely, a large number of researchers are working on security of data in cloud computing, because the trustworthy environment of the technology is the most required thing or a condition to gain confidence of users (Duarte et al. 2016). ...
Cloud computing is a major blooming technology which has numerous applications in today’s market and is rightly so hyped. Images are a major part of today’s internet data traffic, especially due to widespread social media, and hence, its security is crucial. However, in the present scenario, the images in cloud are a major issue in terms of security. Since the user who has uploaded the image has no control over the security of images, the cloud provider has to ensure maximum security in terms of authentication and prevention from attacks. The main objective of this paper is to provide a method to enhance the safety of images on cloud. This paper presents an idea of securing images on cloud platform using biometric authentication. Different steps involved in biometric authentication and secure upload and access of images are explained, and integration of all the steps is done at the end as a case study which puts light on the whole process in which methods are best-regarding results and compatibility. The proposed algorithm in this paper presents the idea of authentication of images in two basic steps of image compression using standard discrete wavelet transform method followed by image encryption using the hybrid method of SHA and blowfish. This image is then stored into the database of cloud and accessed whenever the user requests it. A structured and comprehensive view of encryption methods, types of biometrics and to secure data as well as images is provided in this paper.
... To achieve our formulated design goals and considering the identified meta-requirements for a purposeful design of a remote monitoring system for elderly people, we experimented with a series of different hardware/software alternatives. We finally opted for a Raspberry Pi based system-a $40 minicomputer of the size of a credit card running a Debian-based operating system-as the hardware has proven to be sufficiently reliable for smart home applications (Jain et al. 2014), offers a good value for money (Duarte et al. 2016), and can easily be extended with specific onboard accessories and any other standard, off-theshelf component (e.g. web cams, motion sensors, navigation modules, displays etc.). ...
Demographic change and continuously increasing spending on public health have intensified the public debate as well as deliberations on the development and deployment of new assistive technologies for health, independent living, and well-being for senior citizens. Other than large-scale, policy-driven health initiatives that envision ambitious and risky "grand designs", in this paper we illustrate the case of a grassroots-like project which used Action Design Research (ADR) as guiding research paradigm to produce a low-cost, yet effective, monitoring system for people with mild cognitive impairments or dementia. Besides a description of meta-requirements and solution components, we also identify general implications for future research. In particular, we explain how an ADR-inspired approach to social innovation could be a useful alternative to large-scale, policy-driven health initiatives to increase the time-to-market of new solutions, pre-test new use cases, and to enhance accessibility and affordability of assistive technologies for the local community.
... Even though retinal styles can be altered in instance of diabetes, Glaucoma or retinal degenerative disorders, the retina typically remains unaffected from birth till dying. Due to its unique and unchanging nature, the retina seems to be the maximum precise and dependable biometric [8]. Those experiment the unique biometric pattern in every body's iris, and suit it towards a positive range of particular identifying marks that set every person apart from all people else. ...
Biometrics refers to metrics related to human characteristics. Biometrics is a realistic authentication used as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are then measurable, distinctive characteristics used to label and describe individuals. Biometric authenticators are frequently labeled as behavioral as well as physiological characteristics. Physiological characteristics are related to the shape of the body. By utilizing biometrics a man could be distinguished in view of "who she/he is" instead of "what she/he has" (card, token, scratch) or "what she/he knows" (secret key, PIN).In this paper, the fundamental concentrate is on the different biometrics and their applications.
Objectives To study and compare different types of biometric systems and to obtain the result for the same, this paper has discussed the need of biometrics, ways of performing it and the best type of biometrics that should be implemented. Methods and findings: We used various statistics, graphical and tabular representations for showing data studied from different papers and reviewing them. Instances of infringements of right to privacy and protection of personal data are proliferating. Biometric systems are identity authentication systems for information assurance and protection via biological traits since they are unique. Technology is rapidly advancing in every field and choosing passwords are not enough. Biometric systems are the best approach to keep data safe, and it also makes the accessing of data simple. Everything has its own pros and cons so; we will be discussing the pros and cons of various biometric technologies in order to determine the best among them.KeywordsIris recognitionAuthenticationEnrolmentRecognitionFeature extractionTemplate matching
At present, modern technologies are increasingly coming to the fore, including the area of entry security. Electronic access control systems that use RFID to identify people have become popular. However, as the name suggests, electricity is needed to operate them. There may be a power failure problem, causing the system to malfunction and entry is not allowed. Therefore, classic pin tumbler locks are used as a backup for electrical systems. Therefore, it is important to keep in mind the correct choice of pin tumbler locks, as these can be easily overcome, unlike the electronic access control system with RFID. The article deals with foreign research aimed at overcoming the electronic access control system with RFID and completed tests at the Faculty of Security Engineering aimed at overcoming pin tumbler locks.
New assistive technology (AT) is at our disposal for improving the everyday life of people in need. Yet, the current way how AT is produced and provisioned is hindering certain marginalised groups in the population, particularly elderly people, to get access to it. To expedite time-to-market, reduce costs, and increase accessibility to otherwise unattainable AT, we explore if do-it-yourself (DIY) could be a feasible and desirable alternative to commercial applications. We provide answers to the following research questions: (1) For whom does the DIY approach work in the context of assistive technology? (2) Under which circumstances do DIY work? and (3) How can researchers make DIY a satisfying experience? The evidence we collected during the “iCare” project suggests that DIY attracts both, elderly people with a need-based motive and a hedonic motive. It also shows that a participatory approach and an early engagement with potential users, their family members, and informal caregivers is beneficial for improving design and use-related aspects of the AT and the DIY intervention.
The aim of this chapter is to demonstrate the simulation process of parking of a car-like autonomous vehicle in a multi-level garage. Space complexity is one of the major problems that is been addressed today in the construction field. In order to overcome this problem in the context of parking spaces multi-level garages are been extensively constructed. The chapter presents an approach to autonomous parking in multi-level garages.
The Vehicle uses a static off-line map of the garage to navigate inside the garage. The vehicle navigates inside the garage until an empty parking space is detected. Once an empty parking space is detected the vehicle parks itself in the empty slot. The Vehicle uses an Inertial Measurement Unit (IMU) and odometer to localize itself inside the garage. Laser beams are mounted in front of the car on both the left and right extremes to detect the state of a parking space.
The Autonomous vehicle is modelled and imported in a simulation environment called Gazebo which runs alongside ROS. The Autonomous vehicle consists of two lasers, a 6-Axis Inertial Measurement Unit (IMU), Odometer which is also modelled and imported in Gazebo. ROS serves as a platform to run the developed algorithm on the vehicle in Gazebo. The language to do programming is python.
While the application of IT in automation gains traction, mostly motivated by the introduction of Service Orientated Approaches and Multiagent modelling, it is sometimes unclear to practitioners what is the full potential and boundaries of such concepts and technologies. The FP7 IDEAS project is focused in the design and development of Multiagent systems in a Mechatronic context which, to a great extent, implies that Mechatronic Agents must consider and respect mechanical/physical constraints while delivering the widely acknowledged (yet elusively demonstrated) characteristics that may render Agent-based control unique in respect to tolerance to disturbances, plug-ability and scalability. In this context, the present paper details the preliminary proof of concept prototype that validates the IDEAS Mechatronic Agent Architecture. The focus of this early demonstrator is to enlighten on how self-organization, inspired by the Evolvable Assembly System (EAS) Paradigm, can be exploited towards promoting the above mentioned characteristics. The main lessons learned, open points and future developing directions are distilled as the prototype is presented.
Multimodal biometric systems are commonly believed to be more robust to spoofing attacks than unimodal systems, as they combine information coming from different biometric traits. Recent work has shown that multimodal systems can be misled by an impostor even by spoofing only one biometric trait. This result was obtained under a `worst-case` scenario, by assuming that the distribution of fake scores is identical to that of genuine scores (i.e. the attacker is assumed to be able to perfectly replicate a genuine biometric trait). This assumption also allows one to evaluate the robustness of score fusion rules against spoofing attacks, and to design robust fusion rules, without the need of actually fabricating spoofing attacks. However, whether and to what extent the `worst-case` scenario is representative of real spoofing attacks is still an open issue. In this study, we address this issue by an experimental investigation carried out on several data sets including real spoofing attacks, related to a multimodal verification system based on face and fingerprint biometrics. On the one hand, our results confirm that multimodal systems are vulnerable to attacks against a single biometric trait. On the other hand, they show that the `worst-case` scenario can be too pessimistic. This can lead to two conservative choices, if the `worst-case` assumption is used for designing a robust multimodal system. Therefore developing methods for evaluating the robustness of multimodal systems against spoofing attacks, and for designing robust ones, remain a very relevant open issue.
Most biometric systems deployed in real-world applications are unimodal.
Using unimodal biometric systems have to contend with a variety of problems
such as: Noise in sensed data; Intra-class variations; Inter-class
similarities; Non-universality; Spoof attacks. These problems have addressed by
using multibiometric systems, which expected to be more reliable due to the
presence of multiple, independent pieces of evidence.
Unimodal biometric systems have to contend with a vari-ety of problems such as noisy data, intra-class variations, re-stricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. Some of these limitations can be addressed by deploying multimodal biometric systems that integrate the evidence presented by multiple sources of in-formation. This paper discusses the various scenarios that are possible in multimodal biometric systems, the levels of fusion that are plausible and the integration strategies that can be adopted to consolidate information. We also present several examples of multimodal systems that have been de-scribed in the literature.
The emerging paradigm of agent-based computation has revolutionized the building of intelligent and decentralized systems. The new technologies met well the requirements in all domains of manufacturing where problems of uncertainty and temporal dynamics, information sharing and distributed operation, or coordination and cooperation of autonomous entities had to be tackled. In the paper software agents and multi-agent systems are introduced and through a comprehensive survey, their potential manufacturing applications are outlined. Special emphasis is laid on methodological issues and deployed industrial systems. After discussing open issues and strategic research directions, we conclude that the evolution of agent technologies and manufacturing will probably proceed hand in hand. The former can receive real challenges from the latter, which, in turn, will have more and more benefits in applying agent technologies, presumably together with well-established or emerging approaches of other disciplines.
A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed. The system is tested on a highly challenging database comprising over 10,500 real and fake images acquired with five sensors of different technologies and covering a wide range of direct attack scenarios in terms of materials and procedures followed to generate the gummy fingers. The proposed solution proves to be robust to the multi-scenario dataset, and presents an overall rate of 90% correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake. This last characteristic provides the method with very valuable features as it makes it less intrusive, more user friendly, faster and reduces its implementation costs.
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.
Geometric measurements of the human hand have been used for identity authentication in a number of commercial systems. Yet, there is not much open public literature addressing research issues underlying hand geometry-based identity authentication. This work is our attempt to draw attention to this important biometric by designing a prototype hand geometrybased identity authentication system. We also present our preliminary verification results based on hand measurements of 50 individuals captured over a period of time. The results are encouraging and we plan to address issues to improve the system performance.
The new market trends are very different, so it is crucial to the companies improve the tools and capabilities that allow themselves readjust rapidly and effectively to the news market changes and to the new requirements. In order to facilitate this process, it is proposed in this paper an agent based implementation that can provide to the existent systems the capacity to quickly adapt and reconfigure using standard technology. The proposed framework provides an intelligent tool to autonomously help the configuration when a production operator pretends to introduce a new variant of product in runtime and consult important information provided by the system to monitor execution.
Biometrics have been proposed as a replacement for passwords, overcoming some inherent flaws in password technology1. Trusting completely in biometric technology can lead to problems of its own, though. This article explores the flaws inherent in both password and biometric technologies, and suggests that they can be used in conjunction with each other to reinforce the security of verification applications.
This paper describes a fingerprint system for a secure perimeter, allowing access to only those people who are identified by the officials using bio-metric identification of finger print. The system would work in both online and offline mode. System also employs Power over Ethernet. The goal of this project is to develop a complete system for fingerprint identification. The fingerprint scanning device utilizes serial communication. This device will be connected to the microprocessor using RS-232 ports. The system will consist of an LM3S6965 microprocessor, LCD display, fingerprint sensor, electronic door strike, and MCU to USB PC interfacing. Software Code for the PC allows the owner to register and maintain the attendance record for finger-prints and monitor door entry. LCD's and LED's will be used to display whether or not access was granted or denied.
With the current prevalence of Ubiquitous Computing, more specifically Internet of Things, almost every other appliance aims to exhibit smart behavior and expose it through internet connectivity, resulting in a plethora of sensors that expose environmental information online. As a direct result, large quantities of data are pouring online waiting to be processed. Our paper addresses this problem through an architecture which handles storage, analysis and processing of large amounts of data and can scale accordingly, providing a corner stone for Internet of Things.
The term biometrics has been hard to escape recently, with numerous articles being published discussing the advantages and disadvantages of the technology1 and 2. Much of this discussion has come about due to the level of research and interest shown in large scale implementations of the technology by the US and UK Governments3 and 4 and European Union.5 However, few articles to date have discussed the fundamental operation of biometrics and the subsequent issues that arise when developing a biometric technique. This article focuses upon describing the biometric process from a lower level of abstraction, and introduces a number of design features that play an inherent role in the security provided by a biometric approach.
The vulnerability of biometric devices to spoof attacks and various anti-spoofing measures are discussed. Spoof attacks involve the use of an artificial biometric sample to gain unauthorized control. Various anti-spoofing measures have been developed to counteract this problem of spoofing. These anti-spoofing techniques include addition of supervision, password, smart cards, enrolment of several biometric samples, multi-modal biometrics, and liveness testing.
This paper deals with the design of a biometric security system based upon the fingerprint and speech technology. In the first chapter there are the biometric security systems and a concept of an integration of the both technologies introduced. Then the fingerprint technology followed by the speech technology is shortly described. There are discussed some basic principles of each of the technologies.
The use of fingerprints for identification has been employed in law enforcement for about a century. A much broader application
of fingerprints is for personal authentication, for instance to access a computer, a network, a bank-machine, a car, or a
home. The topic of this chapter is fingerprint verification, where “verification” implies a user matching a fingerprint against
a single fingerprint associated with the identity that the user claims. The following topics are covered: history, image processing
methods, enrollment and verification procedures, system security considerations, recognition rate statistics, fingerprint
capture devices, combination with other biometrics, and the future of fingerprint verification.
It has been shown that fingerprint scanners can be deceived very easily, using simple, inexpensive techniques. In this work, a countermeasure against such attacks is enhanced, that utilizes a wavelet based approach to detect liveness, integrated with the fingerprint matcher. Liveness is determined from perspiration changes along the fingerprint ridges, observed only in live people. The proposed algorithm was applied to a data set of approximately 58 live, 50 spoof and 28 cadaver fingerprint images captured at 0 and 2 s, from each of three different types of scanners, for normal conditions. The results demonstrate perfect separation of live and not live for the normal conditions. Without liveness module the commercially available verifinger matcher is shown to give equal error rate (EER) of 13.85% where false reject rate is calculated for genuine-live users and false accept rate is for genuine-not live, imposter-live and imposter-not live. The integrated system of fingerprint matcher and liveness module reduces EER to 0.03%. Results are also presented for moist and dry fingers simulated by glycerin and acetone, respectively. The system is further tested using gummy fingers and various deliberately simulated conditions including pressure change and adding moisture to the spoof to analyze the strength of the liveness algorithm.
In this paper, we address the security of multimodal biometric systems when one of the modes is successfully spoofed. We propose two novel fusion schemes that can increase the security of multimodal biometric systems. The first is an extension of the likelihood ratio based fusion scheme and the other uses fuzzy logic. Besides the matching score and sample quality score, our proposed fusion schemes also take into account the intrinsic security of each biometric system being fused. Experimental results have shown that the proposed methods are more robust against spoof attacks when compared with traditional fusion methods.
Perspiration phenomenon is very significant to detect liveness of a finger. However, it requires two consecutive fingerprints to notice perspiration, and therefore it may not be suitable for real-time authentications. Some other methods in the literature need extra hardware to detect liveness. To alleviate these problems, we propose a new ridgelet transform-based method which needs only one fingerprint to detect liveness. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Ridgelet transform allows representing singularities along lines in a more efficient way than the wavelets. Fingerprint is an oriented texture pattern of ridge lines; hence naturally ridgelets are more suitable for fingerprint processing than the wavelets. We use ridgelet energy and co-occurrence signatures to characterize fingerprint texture using our databases consisting of real and spoof fingerprints. Dimensionalities of feature sets are reduced by running principal component analysis (PCA) algorithm. Ridgelet energy and co-occurrence signatures are independently tested on various classifiers such as: neural network, support vector machine and K-nearest neighbor. Finally, we fuse all the classifiers using the “mean rule” to build an ensemble classifier. Fingerprint databases consisting of 185 real, 90 fun-doh and 150 gummy fingerprints are created. Multiple combinations of materials are used to create casts and moulds of spoof fingerprints. Experimental results indicate that, the performance of a new liveness detection approach is very promising, as it needs only one fingerprint and no extra hardware to detect vitality.
Cloud Computing is rising fast, with its data centres growing at an
unprecedented rate. However, this has come with concerns over privacy,
efficiency at the expense of resilience, and environmental sustainability,
because of the dependence on Cloud vendors such as Google, Amazon and
Microsoft. Our response is an alternative model for the Cloud
conceptualisation, providing a paradigm for Clouds in the community, utilising
networked personal computers for liberation from the centralised vendor model.
Community Cloud Computing (C3) offers an alternative architecture, created by
combing the Cloud with paradigms from Grid Computing, principles from Digital
Ecosystems, and sustainability from Green Computing, while remaining true to
the original vision of the Internet. It is more technically challenging than
Cloud Computing, having to deal with distributed computing issues, including
heterogeneous nodes, varying quality of service, and additional security
constraints. However, these are not insurmountable challenges, and with the
need to retain control over our digital lives and the potential environmental
consequences, it is a challenge we must pursue.
The spread of the Internet and the evolution of mobile communication, have created new possibilities for software applications such as ubiquitous computing, dynamic supply chains and medical home care. Such systems need to operate in dynamic, heterogeneous environments and face the challenge of handling frequently changing requirements; therefore they must be flexible, robust and capable of adapting to the circumstances. It is widely believed that multi-agent systems coordinated by selforganisation and emergence mechanisms are an effective way to design these systems. This paper aims to define the concepts of self-organisation and emergence and to provide a state of the art survey about the different classes of self-organisation mechanisms applied in the multi-agent systems domain. Furthermore, the strengths and limits of these approaches are examined and research issues are provided.
Biometric recognition refers to an automatic recognition of individuals based on a feature vector (s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on "who she/he is" rather then "what she/he has" (card, token, key) or "what she/he knows" (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal, and their advantages and disadvantages, will be presented.
How Iris Recognition Works
- J Daugman
AgentLink Second Technical Forum Group Self-Organisation in Multi-Agent
- G D M Serugento
- M.-P Gleizes
- A Karageorgos
Eye Macro - Iris Detail
- N Fedele
Face Detection and Recognition in C# using EmguCV 3.0 (OpenCV Wrapper)
- A A Opeyemi
About Fingerprint Ring Engraving
- Larson Jewelers