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Electronic documents constitute specific units of information, and protecting them against unauthorized access is a challenging task. This is because a password protected document may be stolen from its host computer or intercepted while on transfer and exposed to unlimited offline attacks. The key issue is, therefore, making document passwords hard to crack. We propose to augment a common text password authentication interface to encrypted documents with a biometric facial identity verification providing highly personalized security mechanism based on pseudo-identities. In consequence the encrypted document can be unlocked with the legitimate user’s face, while for everyone else stays encrypted with a hard to crack text password. This paper makes two contributions: (1) The proposed scheme enables password autofill without referring to any external service, which significantly limits the possibilities of an attack by adversaries when opening, reading and editing the protected document, (2) By the adoption of biometric verification techniques enabling fine-tuning of false acceptance and false rejection rates, it provides for responsible adaptation to users.

Estimating Population Abundance of Burying Beetles Using Photo-Identification and Mark-Recapture Methods

Successful conservation and management of protected wildlife populations require reliable population abundance data. Traditional capture-mark-recapture methods can be costly, time-consuming, and invasive. Photographic mark-recapture (PMR) is a cost-effective, minimally invasive way to study population dynamics in species with distinct markings or color patterns. We tested the feasibility and the application of PMR using the software Hotspotter to identify Nicrophorus spp. from digital images of naturally occurring spot patterns on their elytra. We conducted a laboratory study evaluating the identification success of Hotspotter on Nicrophorus americanus (Olivier, 1790) and Nicrophorus orbicollis (Say, 1825) before implementation of a mark-recapture study in situ. We compared the performance of Hotspotter using both ‘high-quality’ and ‘low-quality’ photographs. For high-quality photographs, Hotspotter had a false rejection rate of 2.7–3.0% for laboratory-reared individuals and 3.9% for wild-caught individuals. For low-quality photographs, the false rejection rate was much higher, 48.8–53.3% for laboratory-reared individuals and 28.3% for wild-caught individuals. We subsequently analyzed encounter histories of wild-caught individuals with closed population models in Program MARK to estimate population abundance. In our study, we demonstrated the utility of using PMR in estimating population abundance for Nicrophorus spp. based on elytral spot patterns.

Auditory Device Voice Activity Detection Based on Statistical Likelihood-Ratio Order Statistics

This paper proposes a technique for improving statistical-model-based voice activity detection (VAD) in noisy environments to be applied in an auditory hearing aid. The proposed method is implemented for a uniform polyphase discrete Fourier transform filter bank satisfying an auditory device time latency of 8 ms. The proposed VAD technique provides an online unified framework to overcome the frequent false rejection of the statistical-model-based likelihood-ratio test (LRT) in noisy environments. The method is based on the observation that the sparseness of speech and background noise cause high false-rejection error rates in statistical LRT-based VAD—the false rejection rate increases as the sparseness increases. We demonstrate that the false-rejection error rate can be reduced by incorporating likelihood-ratio order statistics into a conventional LRT VAD. We confirm experimentally that the proposed method relatively reduces the average detection error rate by 15.8% compared to a conventional VAD with only minimal change in the false acceptance probability for three different noise conditions whose signal-to-noise ratio ranges from 0 to 20 dB.

Biometric Secured Electronic Health Record

Lot of Hospitals around the world are going through transformation from paper based to Electronic Health record system which can be accessed from anywhere. But with such Electronic health record, security is very much needed towards avoiding hackers and unauthorized personnel to access the medical record pretending as doctor or patient. Lot of research been conducted in regards to an authentication of the biometric system and security on the digital electronic health records of the health care organization. In such biometric system, there has been an increase in the false rejection ratio due to a slight difference in the positioning of the finger on the biometric scanner. The small wounds and scratches on the fingers may also lead to the false rejection of the legitimate user. So accordingly the authors in this research have developed innovative and enhanced technology of the frame based biometric authentication system by segmenting the fingerprint image towards authenticating the medical personnel. This method reduces the False Rejection Ratio (FRR) and False Acceptance Ratio (FAR) compared to neighbouring nodal and data centric method. In addition, with the frame based biometric authentication, the authors have also developed level of strictness for doctor's and patient's based on placement of finger in biometric scanner. Lastly, the authors have also developed an application which integrates Frame based biometric methodology along with RFID and GSM for access of records in a secured way and also to provide a better treatment and medicines for incoming patients.

EAgeBioS: Enhanced Biometric System to handle the Effects of Template Aging

Biometric Systems are well-known security systems that can be used anywhere for authentication, authorization or any kind of security verifications. In biometric systems, the samples are trained first and then it can be used for testing in long runs. Many recent researches have shown that a biometric system may fail or get compromised because of the aging of the biometric templates. The fact that temporal duration affects the performance of the biometric system has shattered the belief that iris does not change over lifetime. This is also possible in the case of iris. So, the main focus of this work is to analyze the effect of aging and also to propose a new system that can deal with template aging. We have proposed a new iris recognition system with an image enhancement mechanism and different feature extraction mechanisms. In this work, three different features are extracted, which are then fused to be used as one. The full system is trained on a dataset of 2500 samples for the year 2008 and testing is done in three different phases (i) No-Lapse, (ii) 1-Year Lapse and (iii) 2-Year Lapse. A portion of the ND-Iris-Template-Aging dataset [11] is used with a period of three years lapse. Results show that the performance of the hybrid classifier AHyBrK [17] is improved as compared to KNN and ANN and the effect of aging in terms of degraded performance is clear. The performance of this system is measured in terms of False Rejection Rate, Error Rate, and Accuracy. The overall performance of AHyBrK is 51.04% and 52.98% better than KNN and ANN respectively in terms of False Rejection Rate and Error Rate whereas the accuracy of this proposed system is also improved by 5.52% and 6.04% as compared to KNN and ANN respectively. This proposed system also achieved high accuracy for all the test phases.

Similarity assessment of quality attributes of biological medicines: the calculation of operating characteristics to compare different statistical approaches

The comparison of quality attributes is a key element in the evaluation of both biosimilars and manufacturing process changes for biological medicines. Different statistical approaches are proposed to facilitate such evaluations. However, there is no regulatory consensus on a quantitative and scientifically justified definition and an underlying hypothesis of a statistically equivalent quality. The latter is essential to calculate operating characteristics of different approaches. This article proposes a hypothesis for establishing statistically equivalent quality which is concordant with current regulations. It also describes a tool which allows comparisons of different statistical approaches or tests by calculating the operating characteristics for false acceptance and false rejection rates of a claim for statistically equivalent quality. These error rates should be as low as possible to allow a meaningful application of a statistical approach in regulatory decision making. The described tool can be used to compare different statistical approaches for their suitability and may also facilitate the discussion and development of statistical approaches for comparing quality attributes in similarity assessments in general.

Studi Perbandingan Metode Wavelet Dalam Speech Recognition Pada Sistem Akses Personel

Penelitian tentang speech recognition terus berkembang terkait identifikasi personel. Pada penelitian ini, kami melakukan studi perbandingan metode wavelet dalam speech recognition. Pada penelitian ini teknologi speech recognition berbasiskan wavelett dan neuro fuzzy. Beberapa parameter yang digunakan dalam penelitian ini adalah sampel suara dengan frekuensi sampling 8000 Hz dan 8 bit per sampel dengan filter wavelet High Pass Filter (HPF). Level dekomposisi menggunakan wavelet daubechies, symlet dan coiflet. Nilai thereshold filter wavelet identifikasi personel 57,72%, False Rejection Rate (FRR) 40% dan running time 1,97 detik. Untuk nilai thereshold identifikasi personel 100%, False Rejection Rate (FRR) 0% dan running time 5,43 detik didapatkan pada level dekomposisi 5 pada wavelet db1. Identifikasi tipe wavelet dari yang terbaik adalah coiflet, symlet dan daubechies karena coif2 level 2 memberikan identifikasi 60,00%, FRR 40,00% dan running time 1,97 detik