Search results for: Signature biometric.

Authors: Abhay Utpat, R. B. Ingle, M. R. Nandgaonkar

Abstract:

The vibrations produced by a single point defect on various parts of the bearing under constant radial load are predicted by using a theoretical model. The model includes variation in the response due to the effect of bearing dimensions, rotating frequency distribution of load. The excitation forces are generated when the defects on the races strike to rolling elements. In case of the outer ring defect, the pulses generated are with periodicity of outer ring defect frequency where as for inner ring defect, the pulses are with periodicity of inner ring defect frequency. The effort has been carried out in preparing the physical model of the system. Different defect frequencies are obtained and are used to find out the amplitudes of the vibration due to excitation of the bearing parts. Increase in the radial load or severity of the defect produces a significant change in bearing signature characteristics.

Keywords: Condition monitoring, defect frequency, rolling element, vibration response.

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Authors: Ardhendu Behera, Denis Lalanne, Rolf Ingold

Abstract:

This paper proposes a method, combining color and layout features, for identifying documents captured from lowresolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. The combined color and layout features are arranged in a symbolic file, which is unique for each document and is called the document-s visual signature. Our identification method first uses the color information in the signatures in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining search space. Finally, our experiment considers slide documents, which are often captured using handheld devices.

Keywords: Document color modeling, document visual signature, kernel density estimation, document identification.

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Authors: A-Q. Nguyen. A. Amrhar, J. Zambrano, G. Brown, O.A. Yeste-Ojeda, R. Jr. Landry

Abstract:

Since the presence of Next Generation Air Transportation System (NextGen), Automatic Dependent Surveillance-Broadcast (ADS-B) has raised specific concerns related to the privacy and security, due to its vulnerable, low-level of security and limited payload. In this paper, the authors introduce and analyze the combination of Pulse Amplitude Modulation (PAM) and Phase Shift Keying (PSK) Modulation in conventional ADS-B, forming Secure ADS-B (SADS-B) avionics. In order to demonstrate the potential of this combination, Hardware-in-the-loop (HIL) simulation was used. The tests' results show that, on the one hand, SADS-B can offer five times the payload as its predecessor. This additional payload of SADS-B can be used in various applications, therefore enhancing the ability and efficiency of the current ADS-B. On the other hand, by using the extra phase modulated bits as a digital signature to authenticate ADS-B messages, SADS-B can increase the security of ADS-B, thus ensure a more secure aviation as well. More importantly, SADS-B is compatible with the current ADS-B In and Out. Hence, no significant modifications will be needed to implement this idea. As a result, SADS-B can be considered the most promising approach to enhance the capability and security of ADS-B.

Keywords: ADS-B authentication, ADS-B security, NextGen ADS-B, PSK signature, secure ADS-B.

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

Abstract:

In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: Muhammad F. Yaqub, Iqbal Gondal, Joarder Kamruzzaman

Abstract:

Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Keywords: Envelop detection, machine defect frequency, multiple faults, machine health monitoring.

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Authors: Ammar M. Hassan, Ayoub Al-Hamadi, Yassin M. Y. Hasan, Mohamed A. A. Wahab, Bernd Michaelis

Abstract:

Because of the great advance in multimedia technology, digital multimedia is vulnerable to malicious manipulations. In this paper, a public key self-recovery block-based video authentication technique is proposed which can not only precisely localize the alteration detection but also recover the missing data with high reliability. In the proposed block-based technique, multiple description coding MDC is used to generate two codes (two descriptions) for each block. Although one block code (one description) is enough to rebuild the altered block, the altered block is rebuilt with better quality by the two block descriptions. So using MDC increases the ratability of recovering data. A block signature is computed using a cryptographic hash function and a doubly linked chain is utilized to embed the block signature copies and the block descriptions into the LSBs of distant blocks and the block itself. The doubly linked chain scheme gives the proposed technique the capability to thwart vector quantization attacks. In our proposed technique , anyone can check the authenticity of a given video using the public key. The experimental results show that the proposed technique is reliable for detecting, localizing and recovering the alterations.

Keywords: Authentication, hash function, multiple descriptioncoding, public key encryption, watermarking.

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Authors: Hidetoshi Nonaka, Masahito Kurihara

Abstract:

In this paper, an authentication system using keystroke dynamics is presented. We introduced pressure sensing for the improvement of the accuracy of measurement and durability against intrusion using key-logger, and so on, however additional instrument is needed. As the result, it has been found that the pressure sensing is also effective for estimation of real moment of keystroke.

Keywords: Biometric authentication, Keystroke dynamics, Pressure sensing, Time-frequency analysis.

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Authors: Gláucya C. Boechat, Jeneffer C. Ferreira, Edson C. B. Carvalho

Abstract:

This paper presents a boarding on biometric authentication through the Keystrokes Dynamics that it intends to identify a person from its habitual rhythm to type in conventional keyboard. Seven done experiments: verifying amount of prototypes, threshold, features and the variation of the choice of the times of the features vector. The results show that the use of the Keystroke Dynamics is simple and efficient for personal authentication, getting optimum resulted using 90% of the features with 4.44% FRR and 0% FAR.

Keywords: Biometrics techniques, Keystroke Dynamics, patternrecognition.

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Authors: Ernst D. Schmitter

Abstract:

There is increasing evidence that earthquakes produce electromagnetic signals observable at the surface in the extremely low to very low freqency (ELF - VLF) range often in advance to the main event. These precursors are candidates for prediction purposes. Laboratory experiments con´¼ürm that material under load emits an electromagnetic signature, the detailed generation mechanisms how- ever are not well understood yet.

Keywords: Earthquakes, ELF, EM signals from material under load, signal propagation in conductors.

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Authors: M.K. Bhuyan, Aragala Jagan.

Abstract:

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.

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Authors: Ali Shojaee Bakhtiari, Ali Asghar Beheshti Shirazi, Amir Sepasi Zahmati

Abstract:

An efficient iris segmentation method based on analyzing the local entropy characteristic of the iris image, is proposed in this paper and the strength and weaknesses of the method are analyzed for practical purposes. The method shows special strength in providing designers with an adequate degree of freedom in choosing the proper sections of the iris for their application purposes.

Keywords: Iris segmentation, entropy, biocryptosystem, biometric identification.

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Authors: O. Onoriode Emoyan, E. Eyitemi Akporhonor, Charles Otobrise

Abstract:

Polycyclic Aromatic Hydrocarbons (PAHs) are formed mainly because of incomplete combustion of organic materials during industrial, domestic activities or natural occurrence. Their toxicity and contamination of terrestrial and aquatic ecosystem have been established. However, with limited validity index, previous research has focused on PAHs isomer pair ratios of variable physicochemical properties in source identification. The objective of this investigation was to determine the empirical validity of Pearson Correlation Coefficient (PCC) and Cluster Analysis (CA) in PAHs source identification along soil samples of different land uses. Therefore, 16 PAHs grouped, as Endocrine Disruption Substances (EDSs) were determined in 10 sample stations in top and sub soils seasonally. PAHs was determined the use of Varian 300 gas chromatograph interfaced with flame ionization detector. Instruments and reagents used are of standard and chromatographic grades respectively. PCC and CA results showed that the classification of PAHs along pyrolitic and petrogenic organics used in source signature is about the predominance PAHs in environmental matrix. Therefore, the distribution of PAHs in the studied stations revealed the presence of trace quantities of the vast majority of the sixteen PAHs, which may ultimately inhabit the actual source signature authentication. Therefore, factors to be considered when evaluating possible sources of PAHs could be; type and extent of bacterial metabolism, transformation products/substrates, and environmental factors such as salinity, pH, oxygen concentration, nutrients, light intensity, temperature, co-substrates, and environmental medium are hereby recommended as factors to be considered when evaluating possible sources of PAHs.

Keywords: Comparative correlation, kinetically, polynuclear aromatic hydrocarbons, thermodynamically- favored PAHs, sources evaluation.

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Authors: Sakthi Priya Balaji R., Vijayendar G.

Abstract:

This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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Authors: Edward Guillen, Daniel Padilla, Adriana Hernandez, Kenneth Barner

Abstract:

Biometrics methods include recognition techniques such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it does not need the prior concern of the observed subject and it can record many biometric features in order to make deeper analysis, but most of the research proposals use high computational cost. This paper shows a gait recognition system with feature subtraction on a bundle rectangle drawn over the observed person. Statistical results within a database of 500 videos are shown.

Keywords: Autentication, Biometrics, Gait Recognition, Human Identification, Security.

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Authors: G. Koukiou, V. Anastassopoulos

Abstract:

In this paper a bank of velocity filters is devised to be used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept from velocity filters. Accordingly, velocity filters are built using the spectral signature of each separate moving object. Experimentation reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the velocity are concerned.

Keywords: Velocity filters, filter banks, 3-D FFT.

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Authors: Girija Chetty, Monica Singh

Abstract:

In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..

Keywords: Biometrics, gait recognition, PCA, LDA, Eigenface, Fisherface, Multivariate Gaussian Classifier

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Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara

Abstract:

The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.

Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

Abstract:

This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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Authors: Carlos Gonzalez

Abstract:

When communicating using private and secure keys, there is always the doubt as to the identity of the message creator. We introduce an algorithm that uses the personal typing rhythm (keystroke dynamics) of the message originator to increase the trust of the authenticity of the message originator by the message recipient. The methodology proposes the use of a Rhythm Certificate Authority (RCA) to validate rhythm information. An illustrative example of the communication between Bob and Alice and the RCA is included. An algorithm of how to communicate with the RCA is presented. This RCA can be an independent authority or an enhanced Certificate Authority like the one used in public key infrastructure (PKI).

Keywords: Personal rhythm, public-key encryption, authentication, digital signature, keystroke dynamics.

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Authors: Andrew Lock, Alastair Allen

Abstract:

Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance ofinvestigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: Biometrics, iris recognition, reversible watermarking.

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Authors: F. Amin, A. H. Jahangir, H. Rasifard

Abstract:

With the widespread growth of applications of Wireless Sensor Networks (WSNs), the need for reliable security mechanisms these networks has increased manifold. Many security solutions have been proposed in the domain of WSN so far. These solutions are usually based on well-known cryptographic algorithms. In this paper, we have made an effort to survey well known security issues in WSNs and study the behavior of WSN nodes that perform public key cryptographic operations. We evaluate time and power consumption of public key cryptography algorithm for signature and key management by simulation.

Keywords: Wireless Sensor Networks, Security, Public Key Cryptography, Key Management.

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Authors: Young Geun Kim, Tae Woo Lee, Changmin Yeo, Jung min Yoo, Yeo Jin Kang, Tack-Joong Kim, Byungjo Jung, Ji Hun Cha, Chan Hoi Hur, Dong-Sup Kim, Ki Jung Park, Han Sung Kim

Abstract:

The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Keywords: mechanical skin damage, optical coherence tomography, tattooed skin

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Authors: Mario Mastriani

Abstract:

This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.

Keywords: Projection, speckle, superresolution, synthetic aperture radar, thresholding, wavelets.

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Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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Authors: Hafiz Gulfam Ahmad, Chuangdong Li, Zeeshan Ahmad

Abstract:

In this paper, we have proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach to reduce the probability of network attacks.

Keywords: Network security, Intrusion detection, Honeypot, Snort, Nmap.

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Authors: Basant Kumar, Animesh Anand, S.P. Singh, Anand Mohan

Abstract:

This paper presents a new spread-spectrum watermarking algorithm for digital images in discrete wavelet transform (DWT) domain. The algorithm is applied for embedding watermarks like patient identification /source identification or doctors signature in binary image format into host digital radiological image for potential telemedicine applications. Performance of the algorithm is analysed by varying the gain factor, subband decomposition levels, and size of watermark. Simulation results show that the proposed method achieves higher watermarking capacity.

Keywords: Watermarking, spread-spectrum, discrete wavelettransform, telemedicine

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Authors: S. Sowmyayani

Abstract:

The advancement of computer-aided design helps the medical force and security force. Some applications include biometric recognition, elderly fall detection, face recognition, cancer recognition, tumor recognition, etc. This paper deals with different machine learning algorithms that are more generically used for any health care system. The most focused problems are classification and regression. With the rise of big data, machine learning has become particularly important for solving problems. Machine learning uses two types of techniques: supervised learning and unsupervised learning. The former trains a model on known input and output data and predicts future outputs. Classification and regression are supervised learning techniques. Unsupervised learning finds hidden patterns in input data. Clustering is one such unsupervised learning technique. The above-mentioned models are discussed briefly in this paper.

Keywords: Supervised learning, unsupervised learning, regression, neural network.

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Authors: Olaf Hallan Graven, Lachlan MacKinnon

Abstract:

One major issue that is regularly cited as a block to the widespread use of online assessments in eLearning, is that of the authentication of the student and the level of confidence that an assessor can have that the assessment was actually completed by that student. Currently, this issue is either ignored, in which case confidence in the assessment and any ensuing qualification is damaged, or else assessments are conducted at central, controlled locations at specified times, losing the benefits of the distributed nature of the learning programme. Particularly as we move towards constructivist models of learning, with intentions towards achieving heutagogic learning environments, the benefits of a properly managed online assessment system are clear. Here we discuss some of the approaches that could be adopted to address these issues, looking at the use of existing security and biometric techniques, combined with some novel behavioural elements. These approaches offer the opportunity to validate the student on accessing an assessment, on submission, and also during the actual production of the assessment. These techniques are currently under development in the DECADE project, and future work will evaluate and report their use..

Keywords: E-learning, remote identification, assessment.

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Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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