Risk-Adapted Access Control with Multimodal Biometric Identification

The presented article examines the background of biometric identification. As a technical method of authentication, biometrics suffers from some limitations. These limitations are due to human nature, because skin, appearance and behavior changes more or less continuously in time. Changing patterns affect quality and always pose a significantly higher risk. This study investigated risk adaption and the integration of the mathematical representation of this risk into the whole authentication process. Several biometrical identification methods have been compared in order to find an algorithm of a multimodal biometric identification process as a possible solution to simultaneously improve the rates of failed acceptations and rejections. This unique solution is based on the Adaptive Neuro-Fuzzy Inference System and the Bayesian Theorem

Az emberi észlelésen alapuló mesterséges intelligencia modellezése a személyazonosításban

Nowadays, in the current political and economical environment the identification of the natural persons is a major challenge. The biometrics as a modern branch of science tries to solve these difficulties. For us, in the Applied Biometrics Institute the most difficult task is to generating an operative artificial copy of our biological perceptual system. In this study we examined those soft computing methods which could be applied as an artificial intelligence method for the implementation of the human biological and psychological processes. According to our outlined model, there is a possible way the create operative biometrical identification devices, which are able to implement the cognitive knowledge and to learn like the human beings

A fuzzy logika alkalmazása a multi-modális biometrikus azonosításban

In this paper we presented an algorithm which can be applied in biometrical identification, especially wherever the high level of false rejection is significant. As the biometrics spreads, the basic difficulties of the controller algorithms are leading us to invent an appropriate technique, which is able to adapt and enough flexible to deal with the daily fluctuations. These daily changes may derive from the routines of the usage, the environmental impacts or even the natural lesions and changes of the user's individual biological identification patterns. The fuzzy logic as a soft computing method applies the artificial intelligence, which based on human thinking and behavior. The fuzzy logic involves the linguistic variables instead of exact numerical equations, and makes implications just like human logic. To highlight the results of our experiments we compared that with the classical mean value calculations

A fuzzy logika alkalmazása a multi-modális biometrikus azonosításban

In this paper we presented an algorithm which can be applied in biometrical identification, especially wherever the high level of false rejection is significant. As the biometrics spreads, the basic difficulties of the controller algorithms are leading us to invent an appropriate technique, which is able to adapt and enough flexible to deal with the daily fluctuations. These daily changes may derive from the routines of the usage, the environmental impacts or even the natural lesions and changes of the user's individual biological identification patterns. The fuzzy logic as a soft computing method applies the artificial intelligence, which based on human thinking and behavior. The fuzzy logic involves the linguistic variables instead of exact numerical equations, and makes implications just like human logic. To highlight the results of our experiments we compared that with the classical mean value calculations

Az emberi észlelésen alapuló mesterséges intelligencia modellezése a személyazonosításban

Nowadays, in the current political and economical environment the identification of the natural persons is a major challenge. The biometrics as a modern branch of science tries to solve these difficulties. For us, in the Applied Biometrics Institute the most difficult task is to generating an operative artificial copy of our biological perceptual system. In this study we examined those soft computing methods which could be applied as an artificial intelligence method for the implementation of the human biological and psychological processes. According to our outlined model, there is a possible way the create operative biometrical identification devices, which are able to implement the cognitive knowledge and to learn like the human beings

A mesterséges neurális hálózatok alkalmazásának lehetőségei a biometrikus személyazonosításban

Cikkünkben a mesterséges neurális hálózatok biometriában történő alkalmazhatóságát vizsgáltuk. Bemutattuk, hogy a mesterséges neurális hálók hogyan épülnek fel, mi adja működésük alapját és milyen problémák megoldására alkalmazhatóak. Egy általános, de plasztikus leírással pontról pontra ismertetjük az általunk alkalmazott algoritmus működését, felkeltve az olvasó figyelmét azokra a nehézségekre amiket mi is megtapasztaltunk

Probabilistic Approach and Fuzzy System Based Support of the Railway Stations’ Smart Security System

One of the keystones of the smart city is the transportation. The railway is the crucial part in the main public- and also the goods-transportation today, and the significance will be constantly growing. Nowadays the increase in threats and decrease in the sense of security generates a high need for designing smart and multi-level integrated security systems on the railway stations. The security risk of these territories has risen in the last years, because the public transportation plays an important role in the lives of nowadays people and will grow in the future. That means a rise in incidences of robbery, vandalism and even terrorism. The integration of the conventional systems gives more possibility and reliability for the facility management and the end-users to prevent the aforementioned incidences. The power of the complex (human-electrical-mechanical) system can be usable if in the central monitoring station only qualified and well trained operators work. Because of the difficulty of the multi-level integrated security systems, without suitable and well-trained users and operators the efficiency of the security decrease. Furthermore, the efficiency of the complex system can be lower than the unintegrated conventional realizations, so that’s why it is needed to integrate special smart functions. Managing the smart complex security systems on the aforementioned railway stations are difficult due the human factor and the large number of connections and internal processes. However, the recently created and improved probabilistic approach- and fuzzy system can be a useful mathematical solution for the aforementioned cases. These methods can be used in the full scaled security system, if first – like the Fuzzy logic – an expert level analysis gives enough information about the crucial parts of the system. With them comes the possibility to give and get data from the determined system, and continuously recalculate the factors and – in some cases – it can also be done online. It helps to generate and send prompt information to the facility management, and with it can maximize the fully functional operational efficiency and reduce the hazards. This article gives a useful guideline for the facility management of the smart cities’ railway stations. It declares the main connections with theirs hazards to find the key elements and the in-, and outbound parameters of the smart complex security system. The generated knowledge base will contain also more additional information about the efficiency and the improvement of the system, too

Identification of Radioactive Isotopes Using Cholesky-Decomposition of Matrices

The process of identification of radioactive isotopes using gamma ray spectrum produced by scintillation detectors is a fundamental problem in physics. Military applications also require fast and efficient methods, especially in field conditions, for identifying unknown isotopes. The fundamental problem is the relationship between the observed gamma ray spectrum given by the detector and the real spectrum. This problem can be treated as a mathematical problem. The relationship between the real and the observed spectrum can be described by a linear algebraic equation system. In this article an efficient mathematical procedure is proposed to solve this linear system efficiently

Optimization of Artificial Neural Networks with Genetic Algorithms for Biometric Pattern Recognition

The process of pattern recognition in the biometrics is particularly important. The patterns can differ from each other a lot, and even the samples can be significantly different from the templates. The Artificial Neural Networks can be applied as a universal approximator to recognize the patterns with more flexibility. However the topology of the networks determines the processing time and complexity of the hardware of the physical environments. The Genetic Algorithms can be used with success in optimization problems like in this situation, the topology of the neural network is more optimal if we apply the Genetic Algorithms. This study introduce an algorithm in which a tailor made algorithm correcting the topology to enhance the effectiveness of the process

Analisys of Access Points with the Queue Model for Biometric Access Control in Large Headcount Plants

The scaling of access control systems is usually done with respect to the life protection requirements regarding escape routes. At large headcount areas, the need for biometric identification arises from the security and business needs. Biometric systems can be characterized by probability variables, which can significantly affect the access process. Mathematically, access control is a discrete state space, stochastic process without memory, that can be described by a queue model. This study demonstrates the process model of access control systems and describes the mathematical model that allows for accurate planning and can ensure a successful introduction for access control systems