<p>Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sample application. The demonstration software application is developed by using Verifinger SDK and Microsoft Visual Studio platform. The fingerprint sensor for testing the application is AuthenTec AES2501.</p>

Psychologists have used biometric data since the early 1900s to analyze the emotional responses of such subjects as students, patients with autism, and adults suffering from stress. Biometric data, the recording of physiological responses such as galvanic skin response, heart rate, and eye blinking frequency, shows peaks in emotional response to stimuli in a human’s environment. Galvanic skin response (GSR) is the most potent form of biometric data used for the study of emotional arousal. GSR, if studied in tandem with stimuli, can help researchers identify events in a subject’s environment that trigger emotion. GSR has been used to analyze responses to performance arts, but these studies are typically performed in controlled environments using video-taped performances and not under live performance conditions. Furthermore, this research is more often conducted using dance and not theatre, and often the material studied is less than ½ hour in length. This study combines techniques from several prominent studies of GSR for performing arts response research and applies them to the analysis of a 1 and ½ hour theatrical performance. GSR data is collected from six audience members during live performances of this theatrical work and the subjects are interviewed based on their galvanic skin response recorded during the play. The results of the analysis and interviews are reported to the director and design team of the play in order to inform them of the emotional impact of their work. Such information holds the potential to inform the creative team’s future play-making processes. / text

Σήμερα οι διωκτικές αρχές χρησιμοποιούν αυτόματα βιομετρικά συστήματα αναγνώρισης τα οποία αξιοποιούν βιομετρικά χαρακτηριστικά ατόμων προκειμένου να αναγνωριστούν δράστες εγκλημάτων. Στην παρούσα εργασία έγινε προσπάθεια συσχέτισης αυτής με το αντικείμενο των εγκληματολογικών εργαστηρίων των διωκτικών αρχών. Έτσι δημιουργήθηκε βάση φωνητικών δειγμάτων και κατασκευάστηκε σύστημα αναγνώρισης ομιλητή σε περιβάλλον Matlab με στόχο την μελλοντική αύξηση της βάσης δεδομένων αλλά και την μελλοντική δυνατότητα συνδυασμού: α) εξαγομένων χαρακτηριστικών, β) μεθόδων σύγκρισης των κατανομών φωνητικών δειγμάτων και γ) μεθόδων ταξινόμησης έτσι ώστε να αυξηθεί η απόδοση και να γίνει περισσότερο αξιόπιστο το σύστημα. Το σύστημα που σχεδιάσαμε έχει τα εξής χαρακτηριστικά: α) full automatic, β) open set και γ) text dependent & text in dependent. Από κάθε φωνητικό δείγμα εξάχθηκαν οι mel frequency coefficients με την εργαλειοθήκη Auditory Toolbox, Malcolm Slaney. Η σύγκριση των χαρακτηριστικών των δειγμάτων ομιλίας υλοποιήθηκε με δυο μεθόδους σύγκρισης : Α) Μια διαδικασία που την ονομάσαμε 3Μ (minimum-mean-maximum) η οποία χρησιμοποιεί την Ευκλείδεια απόσταση για την εύρεση αποστάσεων μεταξύ σημείων των κατανομών. Β) Το Wald – Wolfowitz Test (WW-Test ), που στηρίζεται στην θεωρία των γράφων. Τέλος για την ταξινόμηση χρησιμοποιήθηκε ο K-NN ταξινομητής (K – Nearest Neighbor Classifier). Από τα εξαγόμενα αποτελέσματα των μετρήσεων καταλήξαμε στα ακόλουθα συμπεράσματα. Τα όποια σφάλματα προέκυψαν οφείλονται κυρίως στον τρόπο εξαγωγής των mfcc χαρακτηριστικών και λιγότερο στην μέθοδο ταξινόμησης και στον συγκριτή που χρησιμοποιήθηκε. Με την χρήση συνδυαστικά επιπλέον χαρακτηριστικών και ταξινομητών το σύστημα θα γίνει περισσότερο αξιόπιστο. Το σύστημα με μελλοντική αύξηση της βάσης θα μας δώσει ακόμη καλύτερα αποτελέσματα. / Today the law enforcement agencies use automatic biometric identification systems, which utilize human biometric features in order to identify criminals. This thesis was correlated with the objective of forensic laboratories. Hence, a data base of human speech samples and a speaker identification system were developed using the Matlab software. The scope was to increase, in future, the number of the data base samples and to combine features, comparison and classification methods. The system is full automatic, open set, text depended and text independent. From every speech sample, the mel frequency coefficients using the Malcolm Slaney Auditory Toolbox was extracted. The comparison of the speech samples was implemented with two methods: 3M and WW-Test which are based on the graph theory. Finally, the K-NN classifier was used for the classification of the speech samples. From the system evaluation, we conclude that the feature extraction method has the main effect on the system performance. The combination of several features, comparison and classification methods improves the reliability of the system.

Magistro darbe tiriama ekologinių veiksnių įtaka pirmamečių slyvaičių skiepų kokybei. Darbo objektas - bandyme tirtos slyvų veislės 'Viktorija', 'Kometa' ir 'Early Gold', skiepytos į kaukazinę slyvą (Prunus divaricata). Darbo tikslas – palyginti pirmamečių slyvaičių skiepų kokybę auginant juos pastovioje vietoje ir persodinus. Darbo metodai. Dvifaktorinis bandymas atliktas 2008 m. LŽŪU medelyne, karbonatingame, giliau glėjiškame išplautžemyje. Vykdant tyrimą buvo analizuojama skiepų augimo dinamika, nustatytas skiepų aukštis, kamienėlių skersmuo, lapų masė, lapų plotas. Taip pat nustatyta kokybiškų skiepų išeiga. Darbo rezultatai. Tyrimo duomenų analizė parodė, kad intensyviausio slyvaičių skiepų augimo laikotarpio trukmė priklauso nuo veislių ir auginimo sistemų. Aukščiausi per metus užaugo nepersodinti 'Viktorija' medeliai, storiausi – nepersodinti 'Early Gold' skiepai. Didžiausias lapų plotas ir lapų masė buvo nepersodintų 'Kometa' slyvaičių. Kokybiškų pirmamečių medelių kiekį lemia tiek auginimo sistema, tiek ir individualus veislių augumas. / Master work analyse Environmental factors influence on the quality of the vaccine of first year's plum trees. Work object - trial investigated various plum species 'Viktorija', 'Kometa' and 'Early Gold', which were vaccinated into the Caucasian plum (Prunus divaricata). Work purpose - of the test was to compare the effect quality of vaccine for first year's plum trees, which grow in a constant place and for the ones after transplantation. Work method - Two-factor test was conducted in 2008 LŽŪU nursery gardens, albi epihypogleyic luvisols, which are rich in carbonates. During the test, dynamics of growth of the vaccine, the height of the vaccine, shaft diameter, leaf weight and leaf area were all measured. In addition to that, high-quality vaccines yield was also calculated. Work analysis - the analysis of test's data showed that the length of the most intense growth period of vaccine depends on the species and cropping systems. The highest growth level in a year's period was achieved by 'Viktorija' seedlings and the thickest were 'Early Gold' vaccines. 'Kometa' had the biggest leaf area and mass. So in conclusion – the growth quality of first year's trees depends on the cropping system as much as the individual growth properties of the species.

An in-depth study of Advance Passenger Information and Passenger Name Record has never been accomplished prior to the events of September 11 th. It is of great importance to distinguish both of these concepts as they entail different legal consequence. API is to be understood as a data transmission that Border Control Authorities possess in advance in order to facilitate the movements of passengers. It is furthermore imperative that harmonization and inter-operability between States be achieved in order for this system to work. Although the obligations seem to appear for air carriers to be extraneous, the positive impact is greater than the downfalls. / Passenger Name Record access permits authorities to have additional data that could identify individuals requiring more questioning prior to border control clearance. This data does not cause in itself privacy issues other than perhaps the potential retention and manipulation of information that Border Control Authorities may acquire. In essence, bilateral agreements between governments should be sought in order to protect national legislation. / The common goal of the airline industry is to ensure safe and efficient air transport. API and PNR should be viewed as formalities that can facilitate border control clearance and prevent the entrance of potentially high-risk individuals.

Video surveillance is an important tool used in security and environmental monitoring, however, the widespread deployment of surveillance cameras has raised serious privacy concerns. Many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. To identify these individuals for protection, the most reliable approach is to use biometric signals as they are immutable and highly discriminative. If misused, these characteristics of biometrics can seriously defeat the goal of privacy protection. In this dissertation, an Anonymous Biometric Access Control (ABAC) procedure is proposed based on biometric signals for privacy-aware video surveillance. The ABAC procedure uses Secure Multi-party Computational (SMC) based protocols to verify membership of an incoming individual without knowing his/her true identity. To make SMC-based protocols scalable to large biometric databases, I introduce the k-Anonymous Quantization (kAQ) framework to provide an effective and secure tradeoff of privacy and complexity. kAQ limits systems knowledge of the incoming individual to k maximally dissimilar candidates in the database, where k is a design parameter that controls the amount of complexity-privacy tradeoff. The relationship between biometric similarity and privacy is experimentally validated using a twin iris database. The effectiveness of the entire system is demonstrated based on a public iris biometric database. To provide the protected subjects with full access to their privacy information in video surveillance system, I develop a novel privacy information management system that allows subjects to access their information via the same biometric signals used for ABAC. The system is composed of two encrypted-domain protocols: the privacy information encryption protocol encrypts the original video records using the iris pattern acquired during ABAC procedure; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of my framework.

In today's globally expanding business world, protecting the identity and transactions of online consumers is crucial for any company to reach out for new markets. This directs digital information technologies towards the adoption of stronger and more secure authentication schemes. Increasingly, such biometric-based user authentication systems have proven superiority over the traditional ones (such as username/password). Unfortunately, despite the significant advances accomplished in developing biometric technologies, there are several barriers to their wide-scale deployment and application for Internet security. Additionally, introducing new biometrics faces similar barriers and challenges such as expensive equipment, or low-precision sensor technologies. In this research, we propose a novel biometric system for static user authentication, that homogeneously combines mouse dynamics, visual search capability and short-term memory effect. The proposed system introduces the visual search capability, and short-term memory effect to the biometric-based security world for the first time. The use of mouse for its dynamics, and as an input sensor for the other two biometrics, means no additional hardware is required. Experimental evaluation demonstrated the system's effectiveness using variable or one-time passwords. All of these attributes qualify the proposed system to be effectively deployed as a static Web-authentication mechanism. Extensive experimentation was done using 2740 sessions collected from 274 users. Two classification mechanisms were used to measure the performance. Using the first of these, a specially devised neural network model called Divide & Select, an EER of 5.7% was achieved. A computational statistics model showed a higher classification performance; a statistical classifier design called Weighted-Sum produced an EER of 2.1%. The performance enhancement produced as a result of changing the analysis model suggests that with further analysis, performance could be enhanced to an industry standard level. Additionally, we presented a Proof of Concept (POC) system to show the system packaging practicality.

Risk-based authentication is an increasingly popular component in the security architecture deployed by many organizations in mitigating online identity threat. Risk-based authentication uses contextual and historical information extracted from online communications to build a risk profile for the user that can be used to make accordingly authentication and authorization decisions. Existing risk-based authentication systems rely on basic web communication information such as the source IP address or the velocity of transactions performed by a specific account, or originating from a certain IP address. Such information can easily be spoofed and as such put in question the robustness and reliability of the proposed systems. In this thesis, we propose in this work an online risk-based authentication system which provides more robust user identity information by combining mouse dynamics, keystroke dynamics biometrics, and user site actions in a multimodal framework. We propose a Bayesian network model for analyzing free keystrokes and mouse movements involved in web sessions. Experimental evaluation of our proposed model with 24 participants yields an Equal Error Rate of 6.91%. This is encouraging considering that we are dealing with free text and mouse movements and the fact that many web sessions tend to be short. / Graduate

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

Thesis (M.S.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (leaves 69-70).