A Multimodal Biometric Authentication Technique using Fused Features of Finger, Palm and Speech
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.1-8, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.18
Abstract
Biometric verification is a reliable approach that can be used to authenticate a person. Biometric authentication systems depend on unique human characteristics such as face, iris, fingerprint, gait, voice etc. to authenticate persons automatically. Biometrics varies from person to person and this is very sensitive data. This information should be kept safe, if not, severe security and privacy risks may occur. Biometric systems face some challenges like noise and non-universality in the process of establishing identity by using a single biometric trait. The noise in the data sensed from sensors may increase False Acceptance Rate (FAR) of the system where as non-universality may reduce Genuine Acceptance Rate (GAR). Because of this reason biometric systems that use single biometric trait provide less benefits in affording security. In this article, we device a Fused Multimodal system, which uses many biometric traits such as fingerprint, palmprint and voice etc. such that it may provide many advantages over uni-biometric systems such as, greater verification accuracy, larger feature space to accommodate more subjects and more security against spoofing. The newly proposed multimodal authentication system is primarily based on feature extraction using fingerprint, palm print, voice and key generation using RSA. MATLAB tool is used to carry out the experimentation. The performance of multimodal biometrics with RSA has significant improvement which has a GAR of 98% and FAR of 2%.
Key-Words / Index Term
multi-modal biometrics, biometric fusion, fingerprint, palmprint, speech.
References
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Citation
T. Srinivasa Rao, E. Srinivasa Reddy, "A Multimodal Biometric Authentication Technique using Fused Features of Finger, Palm and Speech," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.1-8, 2017.
Monitoring Land Cover of Google Web Service Images through ECOC and ANFIS Classifiers
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.9-16, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.916
Abstract
Image classification is one of the most significant applications for remote sensing imagery which is used in a wide range of applications from military to farm development by the government and private agencies. The proposed work focuses on the land use / land cover classification using advanced supervised classification techniques, Error Correcting Output Code (ECOC) multiclass model classifier and Adaptive Neuro-Fuzzy Inference System (ANFIS) classifier. The samples of different classes such as, vegetation, quarry, water, wasteland and urban area were collected from different locations, refined, and trained on RGB, Gray and HSV color spaces based on the features mean, standard deviation, energy, contrast, entropy, and homogeneity. In ANFIS classifier when the number of inputs is more, the construction of FIS structure causes excessive propagation of number of rules which leads to memory overhead. Owing to this limitation, the number of features was restricted to mean and standard deviation in HSV and RGB color spaces. Based on the performance measures overall accuracy and kappa coefficient, it has been observed that the ECOC classifier produces better results in RGB color space and hence it has been applied on different locations of Tamil Nadu in Google Maps. From the results it has been proved that the ECOC classifier performs well when the ground cover nature is heterogeneous in nature.
Key-Words / Index Term
Error Correcting Output Code (ECOC) multiclass model, True Color Composite Filter, Statistical Features, Textural Features, Google Maps’ Images, Adaptive Neuro-Fuzzy Inference System (ANFIS) classifier
References
[1] S. Pravada, Bharatkar, Rahila Patel, “Assessment of Various Block Truncation Coding Based Remote Sensing Image Classification Techniques,” International Journal of Remote Sensing and GIS, Vol. 2, Issue 1, pp. 52-60, 2013.
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Citation
K.P. Sivagami, S.K. Jayanthi, S. Aranganayagi, "Monitoring Land Cover of Google Web Service Images through ECOC and ANFIS Classifiers," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.9-16, 2017.
Identity Based Distributed Provable Data Possession in Multi Cloud Storage
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.17-21, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.1721
Abstract
Online data integrity checking is very main in cloud storage space. It can make the users verify whether their outsourced data is kept intact without downloading the whole data. In some application scenarios, the clients have to store their data on multi-cloud servers. At the same time, the integrity examination protocol must be efficient in order to save the verify cost. Thus a novel remote data integrity checking model: identity-based distributed provable data possession (ID-DPDP) is proposed for a multi-cloud storage. Based on the bilinear pairing, a concrete ID-DPDP protocol is design. The current paper proposed ID-DPDP protocol is provably protected under the hardness assumption of the standard computational diffie-hellman (CDH) problem. In addition to the structural to the advantages of elimination of certificate management, the ID-DPDP protocol is efficient and flexible. Based on the user authorization, the proposed ID-DPDP protocols perform private verification, delegated verification, and public verification.
Key-Words / Index Term
Cloud computing, Provable data possession, Identity-Based Distributed Provable
References
[1]. P. Ranjima, Sumathi. D , M. Mathew, P. Sivaprakash, "Secure Cloud Storage with Access Control: A Survey", International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.124-126, 2014.
[2]. Erway C.C., Kupcu A., C. Papamanthou “Dynamic Provable Data Possession in multicloud storage”, CCS’09, pp. 2136-233, 2014.
[3]. Seb´e F., Domingo-Ferrer J., Mart´ınez-Ballest´e A., DeswarteY., “Remote Data Integrity checking in Critical Information Infrastructures”, IEEE Transactions on Knowledge and Data Engineering, 2015(8), pp.1-6, 2015.
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[5]. Curtmola R., Khan O., Burns R., Ateniese G., “MR-PDP: Multiple- Replica Provable Data Possession”, ICDCS’09, pp. 415-460, 2016.
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Citation
A. Abinaya, K. Fathima Bibi, "Identity Based Distributed Provable Data Possession in Multi Cloud Storage," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.17-21, 2017.
Role of Balanced Excitation and Inhibition in Modulating the Response Properties of Neural Circuit (Neocognitron)
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.22-26, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.2226
Abstract
The visual Pathway system of our brain is very complicated to understand. The Primary visual cortex is used for the vision in our brain. These processes of vision starting from the retina to visual cortex create a long visual pathway a layer by layer approach and hierarchical connection between them. The brain consists of billions of cells for information processing known as neurons. There are two types of Neuron first is excitatory and second inhibitory .So when the information processing is is required the balance between excitation and inhibition. In this research paper we used the Neocognitron an artificial neural network for visual pathway and demonstrate using this that how role is play using the balancing of excitation and inhibition used for pattern recognition task in the various parameters. In this research paper we demonstrated that how excitation and inhibition ratio can be balanced and what happened when it become imbalanced and impact of pattern recognition and using the Neocognitron Simulator tool developed in .NET platform.
Key-Words / Index Term
Visual Pathway,Neocognitron, Exitation and Inhibition, Artficial Neural Network
References
[1] Fukushima K.: “Artificial vision by multi-layered neural networks: neocognitron and its advances”, Neural Networks, Vol. 37, pp 103-119 ,2013.
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Citation
Arun Singh Chouhan, Manoj Kumar Bhaskar, "Role of Balanced Excitation and Inhibition in Modulating the Response Properties of Neural Circuit (Neocognitron)," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.22-26, 2017.
Image Watermarking Scheme for CT and MRI Scan Images with DWT and SVD Transforms
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.27-32, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.2732
Abstract
Watermarking is the process of hiding digital information in a cover image; the hidden information should, but does not need to, contain a relation to the cover image. The digital watermarking is a field of information hiding which hide the crucial information in the original data for protection illegal duplication and distribution of multimedia data. The discrete wavelet transform (DWT) is an implementation of the wavelet transform using a discrete set of the wavelet scales and translations obeying some defined rules. In this paper we are analyzing about different techniques like DWT, singular value decomposition (SVD) and combination of both with a scaling factor. Apart from all the cases prospective method will gives better output. In the prospective method for the cover image we are implementing SVD to LL band and altering the diagonal singular value coefficients with watermark image by using a scaling factor. The performance of this technique shows improvement in output, peak signal to noise ratio (PSNR) and mean square error (MSE).
Key-Words / Index Term
Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), Peak Signal to Noise Ratio (PSNR),Mean Square Error (MSE)
References
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Citation
V. Rajyalakshmi, K. Ramesh, "Image Watermarking Scheme for CT and MRI Scan Images with DWT and SVD Transforms," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.27-32, 2017.
Computation of External view based Software Metrics: Java Based Tool
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.33-43, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.3343
Abstract
Component based software development (CBSD) strategies have been found to be boon for software development companies. The contribution of past researches in the area of software cost estimation of component based software development was excellent. It has been noticed that the use of the components in software development is hierarchical and this multilevel implementation increases the complexity of the software development. If the depth of the components in hierarchy and their association and aggregation with each other are available in advance then this information helps in estimating the cost and complexity of the software in early stage. The present paper compute the different metrics values during the design phase of the entire life cycle of software development. A component diagram consisting of the various components and their associations has been prepared using ArgoUML software tool. Considering a case of E-learning, our technique has been implemented on this special case, to compute various metrics for analyzing certain results of the software at designing stage which turns out to be the important information to control the development cost and the complexity of the software in advance. By computing external view based metrics we can assess effort estimation and complexity of CBSE at early stage.
Key-Words / Index Term
Software Metrics, Static metrics, dynamic metrics, External view, Component based software
References
[1] S. S Ali, A. Ghafoor and R.A. Paul, “Metrics-guided quality management for component-based software systems”, Proceedings of the 25th Annual International Computer Software and Applications Conference, 2001. COMPSAC 2001, Institute of Electrical and Electronics Engineers (IEEE), Jan 2001, pg. 303-308.
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Citation
P.L. Powar, M.P. Singh, Bharat Solanki, Jawwad Wasat Shareef, "Computation of External view based Software Metrics: Java Based Tool," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.33-43, 2017.
Framing Mining Response of User Interaction According to User’s Demand in Diverse Spatial Data Cloud
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.44-48, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.4448
Abstract
Although we witness routine computer based implementations on daily basis for utilization in real life, still we are further more distanced from better abstractions from spatial data. This paper introduces a framework to mine spatial data that provide better handling of user requirements on real time spatial data. The frameworks use two tier software paradigm which is vital for better mining strategies.
Key-Words / Index Term
Spatial Data Mining, Spatial Database, Data Mining, Interactive Approach, Trigger, Bucket
References
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Citation
Mohd Haseeb Ahmad, Bineet Kumar Gupta, "Framing Mining Response of User Interaction According to User’s Demand in Diverse Spatial Data Cloud," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.44-48, 2017.
Classification Techniques in WEKA: A Review
Review Paper | Journal Paper
Vol.5 , Issue.8 , pp.49-52, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.4952
Abstract
Due to the Internet Revolution there has been a data explosion in recent decades. This is due to the easy availability of Internet at any place and time. Therefore it has become very important to extract relevant information from these explosion of data. Data Mining is extraction or mining of useful information from large amount of data. This can be done manually, semi-automatic or automatically. With an enormous of data stored in databases and data warehouse there is need for development of powerful tools to get meaningful data. Data Mining has many tasks such as Classification, Clustering, etc but Classification has gained much importance. Classification is to classify the data into groups based on its characteristics. WEKA is widely used data mining tool. Here a comparison of various algorithms available in WEKA for classification tasks is done. The dataset considered is iris and various parameters considered for evaluation include accuracy, kappa statistics, mean absolute error and root mean square error. 10 mostly used algorithms are compared. Accuracy is given in terms of CCI (Correctly Classified Instances) and ICI (Incorrectly Classified Instances).
Key-Words / Index Term
Classification, Weka, Data Mining
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Citation
K.H. Wandra, L.P. Gagnani, "Classification Techniques in WEKA: A Review," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.49-52, 2017.
Ethical Aspects of Software Engineering:A wake up call for India
Research Paper | Journal Paper
Vol.5 , Issue.8 , pp.53-62, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.5362
Abstract
Software Engineering has a direct and vigorous effect on individuals, societies, nations and to the whole world. Ignoring or not considering social context of software development can lead to catastrophic consequences. India which has become global leader as its software industry is touching skies can’t sustain it unless its software engineers do not practise better Software design and development practices. Indian government is pushing its software industry further up by its digital India program, creating an ecosystem full of technical manpower, elite technical institutes etc. With the tremendous growth of software development in India, there are also serious threats due to lack of ethics and professionalism.
Key-Words / Index Term
Software Engineering, Ethics, professionalism, Digital India, Cybercrimes
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Citation
Juneed Iqbal, Bilal Maqbool Beigh, "Ethical Aspects of Software Engineering:A wake up call for India," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.53-62, 2017.
Aspect Based Sentiment Analysis with Text Compression
Review Paper | Journal Paper
Vol.5 , Issue.8 , pp.63-66, Aug-2017
CrossRef-DOI: https://doi.org/10.26438/ijcse/v5i8.6366
Abstract
Sentiment Analysis measures the aptitude of people’s opinions through Natural Language Processing, Computational Lingus tics and Text analysis, which are used to extract and analyse subjectivity of information. This paper focuses on Aspect Based Sentiment Analysis, where Text Compression is performed before Aspect Based analysis. For a given huge text is compressed using Text compression model, which is considered as pre-processing task for Aspect Based Sentiment Analysis.
Key-Words / Index Term
Aspect Based sentiment analysis, text compression
References
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Citation
Apoorva T., Pradeep N., "Aspect Based Sentiment Analysis with Text Compression," International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.63-66, 2017.