Experimental Approach On Thresholding Using Reverse Biorthogonal Wavelet Decomposition For Eye Image

This study focus on compression in wavelet decomposition for security in biometric data. The objectives of this research are two folds: a) to investigate whether compressed human eye image differ with the original eye and b) to obtain the compression ratio values using proposed methods. The experiments have been conducted to explore the application of sparsity-norm balance and sparsity-norm balance square root techniques in wavelet decomposition. The eye image with [320x280] dimension is used through the wavelet 2D tool of Matlab. The results showed that, the percentage of coefficients before compression energy was 99.65% and number of zeros were 97.99%. However, the percentage of energy was 99.97%, increased while the number of zeros was same after compression. Based on our findings, the impact of the compression produces different ratio and with minimal lost after the compression. The future work should imply in artificial intelligent area for protecting biometric data

Feature Extraction From Epigenetic Traits Using Edge Detection In Iris Recognition System

Iris recognition is the most accurate biometric identification system on hand. Most iris recognition systems use algorithms developed by Daugman. The performance of iris recognition is highly depends on edge detection. Canny is the edge detectors which commonly used. The objectives of this research are to a) study the edge detection criteria and b)measure the PSNR values in estimating the noise between the original iris feature and new iris template. The eye image with [320x280] dimension is obtained from the CASIA database which has been pre-processed through the segmentation and normalization in obtaining the rubber sheet model with [20x240] in dimension. Once it has been produced, the important information is extracted from the iris. Results show that, the PSNR values of iris feature before and after the process of extraction, was 24.93 and 9.12. For sobel and prewitt, both give 18.5 after the process. Based on our findings, the impact of edge detection techniques produces higher accuracy in iris recognition system

IRIS BIOMETRICS STEGANOGRAPHIC METHOD WITH PIXEL VALUE DIFFERENCING AND HOUGH TRANSFORM FOR HIGHER SECURITY SYSTEM

In biometric security, steganography has become one of the techniques used in defending biometrics data and system. This is due to fraud to the biometric data and illegal activites occured at the biometrics point of system. The biometric data, which in this study, iris, is preprocessed using Hough Transform in producing the iris feature. The pixel values of iris feature is formed, in order to embed the iris feature with the stego key which gained from the cover image (thumbprint from the same trained sample). Studies showed that various techniques of embedding such as least significant bits and pixel value differencing are among popular researches. However, none has been designed for iris implementation in biometrics system. Therefore, a new technique is presented in this paper which integrates pixel value differencing with Hough method in the iris biometrics system. The proposed method modified the pixels values by modifying the most conservative pixels of the block. The theoritical estimation and results produce a scheme which provide a better embedding. The new simulation method provides an embedding capacity, human visual quality and PSNR value is 39.34 dB which is better than the previous methods

A New Model of Securing Iris Authentication Using Steganography

The integration of steganography in biometric system is a solution for enhancing security in iris. The process of biometric enrollment and verification is not highly secure due to hacking activities at the biometric point system such as overriding iris template in database. In this paper, we proposed an enhancement of temporal-spatial domain algorithm which involves the scheme of Least Significant Bits (LSB) as the new model which converts iris images to binary stream and hides into a proper lower bit plane. Here, the stego key, n, will be inserted into the binary values from the plane which concealed the information; where n is the input parameter in binary values which inserted to the iris codes, m. These values produce the output which is the new iris stego image after binary conversion. Theoretically, the proposed model is promising a high security performance implementation in the future

ant-CBIR: a new method for radial furrow extraction in iris biometric

Iris recognition has evolved from first to second generation of biometric systems which capable of recognizing unique iris features such as crypts, collarette and pigment blotches. However, there are still ongoing researches on finding the best way to search unique iris features since iris image contains high noise. The high noise iris images (noisy iris); usually give the biometric systems to deliver erroneous results, leading to categorizations where the actual user is labeled as an impostor. Therefore, this study focuses on a novel method, targeted at overcoming the aforementioned challenge. We present the use of ant colony based image retrieval (ant–CBIR) technique as a successful method in recognizing the radial furrow in noisy iris. This method simulates the behavior of artificial ants, searching for pixel values of radial furrow based on an optimum pixel range. The evaluation of accuracy performance with and without the ant-CBIR application is measured using GAR parameter on UBIRIS.v1. Results show that the GAR is 79.9% with ant-CBIR implementation. The implication of this study contributes to a new feature extraction that has the ability of human-aided computing. Moreover, ant-CBIR helps to provide cost effective, easy maintenance and exploration of a long term data collection

Anonymous Authentication Against Man-In-The-Middle Attack

Evolving enterprise in application and data with flexible and scalable infrastructure in cloud services could improve efficiency and productivity of a business operation. Cloud services also offer resource sharing, data storage and application platform as on-demand services that could reduce the operational expenditure. Nevertheless, increasing usage and accessibility to the cloud services require strong security control to preserve user’s privacy and data integrity due to network communication vulnerabilities. There are many possible attacks that could cause security breach and abuse the user’s identity, leading to illegal access to the server. Man-inthe-middle attack is one of the attacks that can intercept communication between users and collect all users’ information. The attacker can misuse the information and act as a legal user to gain access to the system. It is a big challenge to preserve user’s privacy and provide protection from malicious attack. This paper proposes anonymous authentication scheme to preserve user’s privacy and provide protection to such possible attacks. The proposed scheme also provides secure mutual authentication, anonymity, session key establishment and non-dependency with the third party. The proposed scheme uses password-based authentication as an authentication method with anonymity feature to preserve user’s privacy. Experiment was conducted to test and validate the proposed scheme with man-in-the-middle attack. The result of the experiment shows that the proposed scheme is able to provide the privacy to mitigate and successfully preserve the user’s identity from the attack

ant-CBIR: a new method for radial furrow extraction in iris biometric

Iris recognition has evolved from first to second generation of biometric systems which capable of recognizing unique iris features such as crypts, collarette and pigment blotches. However, there are still ongoing researches on finding the best way to search unique iris features since iris image contains high noise. The high noise iris images (noisy iris); usually give the biometric systems to deliver erroneous results, leading to categorizations where the actual user is labeled as an impostor. Therefore, this study focuses on a novel method, targeted at overcoming the aforementioned challenge. We present the use of ant colony based image retrieval (ant–CBIR) technique as a successful method in recognizing the radial furrow in noisy iris. This method simulates the behavior of artificial ants, searching for pixel values of radial furrow based on an optimum pixel range. The evaluation of accuracy performance with and without the ant-CBIR application is measured using GAR parameter on UBIRIS.v1. Results show that the GAR is 79.9% with ant-CBIR implementation. The implication of this study contributes to a new feature extraction that has the ability of human-aided computing. Moreover, ant-CBIR helps to provide cost effective, easy maintenance and exploration of a long term data collection

A study of ethics and information technology usage among UUM international students / Abdul Manaf Bohari and Nurul Hafizan Mazani

Basically, ethics is a universal entity on guiding beliefs, standards, or ideas that pervades an individual, a group or community of people who are accountable for their actions and behaviors. In the emerging of world of ICT, one is required to behave ethically rights. Ethics of IT users varies according to religions, cultures, and societies; and based on literature review, it depends on beliefs and perceptions. Currently, IT drastically changes the way how ethics is conducted and practised within organizations. Therefore, the main objective of this research is to identify what is perceived as ethical behavior in IT usage. Secondly, this research is to observe the ethics among international students in relation to IT. In order to conduct this research, questionnaire will be used to collect the primary data from respondents, as well as international students of Universiti Utara Malaysia. The data collected will then be analyzed using Statistical Package for Social Science (SPSS) software. This research reveals that, ethics in IT users of different countries such as Indonesia, Thailand, China, Iraq, and Pakistan vary. Mostly, the ethics is based on attitudes and perceptions and to what extent it is said to be ethical in dealing with IT

IRIS RECOGNITION FAILURE IN BIOMETRICS: A REVIEW

More than twenty years iris has been claimed to be the most stable modality in human lifetime. However, the iris recognition produces ‘failure to match’ problem which made the known is unknown user or the genuine is recognized as imposter in the biometric systems. Apparently, failure to recognize the real user as in the database is due to a few assumptions: aging of the sensor, changes in how a person uses the system such as the threshold settings and template aging effect. This paper focuses on template aging effect since it is on ongoing problem faced in iris recognition. Many studies attempted several techniques to overcome the problem in every phase which consists of three general phases: the pre-processing, feature extraction and feature matching. Therefore, the purpose of this paper is to study and identify the problems in iris recognition that lead to failure-to-match in biometrics

Computer Aided System for Brain Abnormalities Segmentation

Detection of abnormalities in brain tissue area in different medical images is inspired by the necessity of high accuracy when dealing with human life. A Variety of diseases occur in brain tissue area such as brain tumour, stroke, infarction, haemorrhage and others. At the present time, the current method that is used for diagnosing those diseases is using a well known digital imaging technique which is Magnetic Resonance Imaging (MRI), though the brain diseases are still difficult to diagnose due to certain circumstances. Thus, Computer Aided System (CAS) is significantly useful due to the fact that it could enhance the results of humans in such domain. It is also important that the false negative cases must be kept at a very low rate. This paper proposes a development of a CAD that implement image processing techniques for segmenting any kind of abnormalities that occur in human brain tissue area. The system is able to determine the patterns and characteristics for each part of particular brain tissue in order to identify any brain abnormalities. The behind idea is that the local textures in the images can reveal the characteristic of abnormalities of the biological structures. Therefore, the system is expected to detect threats in patients and planning for early treatment strategies in the future