A Survey on Data Security and Challenges
Survey Paper | Journal Paper
Vol.08 , Issue.01 , pp.49-54, Feb-2020
Abstract
Big Data has gained attention and become a hot topic in scientific and industrial fields. Big data refers to large amount of data which is difficult to store and process by using traditional data processing application. The digitization of our day to day activities generated petabyte and exabyte of data. The data coming from heterogeneous sources and maximum data is residing in unstructured way. So, Dealing with this enormous data many challenges occur and security issue is one of them. Some other big data challenges are – dealing with huge volume of data, integrating heterogeneous data source, validating data etc. In this paper, we review different challenges and security issues in big data environments.
Key-Words / Index Term
Big data, Challenges, Security, privacy, volume, velocity, veracity, variety, value, exabyte, petabyte
References
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[2] Renu Bhandari, Vaibhav Hans and NeeluJyothi Ahuja, “Big Data Security – Challenges and Recommendations” International Journal of Computer Sciences and Engineering, Volume-4, Issue-1, E-ISSN: 2347-2693.
[3] SnehalataFunde, SurajKarale, LaxmanBharate, “Survey Of Big Data Security”,International Journal Of Current Engineering And Scientific Research, ISSN (PRINT): 2393-8374, (ONLINE): 2394-0697, VOLUME-5, ISSUE-2, 2018.
[4] Sanchita Gupta, AkashKataria, ShubhamRathore, Dharmendra Singh Rajput, “Information Security Issues In Big Data: Solution Using Ppdm (Privacy Preserving Data Mining)”, International Journal of Pharmacy & Technology, Dec-2016, Vol. 8, Issue No.4, 25551-25568.
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[6] Anju Abraham, Shyma Kareem, “Security and Clustering Of Big Data in Map Reduce Framework:A Survey”,International Journal of Advance Research, Ideas and Innovations in Technology, Volume 4, Issue 1, ISSN: 2454-132X.
[7] Yuri Demchenko1, Canh Ngo1, Cees de Laat1, Peter Membrey, Daniil Gordijenko, “Big Security for Big Data: Addressing Security Challenges for the Big Data Infrastructure”.
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Citation
J. Bhattacharya, J. Mistri, R. Biswas, D. Dalui, D. Singh, P. Rakshit, S. Bhattacharyya, "A Survey on Data Security and Challenges", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.49-54, 2020.
Assessment of the Performance of MLP & Hierarchical Clustering Method in the Prediction of Breast Cancer
Research Paper | Journal Paper
Vol.08 , Issue.01 , pp.55-58, Feb-2020
Abstract
Breast cancer is such a type of cancer which can leads to the death of women .in this type of cancer there is excessive growth of cells of the breast tissue are done. Lump, pain or sore, bloody nipple, and change in size are being visible for the case of breast cancer. Breast cancer took places when the tissues of the breast are not in a normal manner and not divided in a proper way. Those abnormal cells make clotted mass tissues, which therefore that becomes a tumor. There are two types of tumors, one is benign, which are not cancerous and that no becomes the cause of anyone‘s death .Another type of tumor is Malignant tumor, that is cancerous and very harmful. The second type of tumor can lead to the death. Soft computing techniques are become popular for the case of medical disease diagnosis and also for the prediction. In this paper we combine the Hierarchical Clustering Method and Multilayer Perceptron to predict of the breast cancer .The accuracy of the proposed methods is 81% for the clustering method and 94% for Multilayer Perceptron.
Key-Words / Index Term
Soft Computing, Breast Cancer, Benign, Malignant, Hierarchical Clustering Method, Multilayer Perceptron
References
[1] Kowsalya, shanmugapriyaa, ― A Survey on Diagnosis Methods of Breast Cancer using Mammography‖ International Journal of Engineering Technology Science and Research , ISSN 2394 – 3386 Vol. 02, Issue 4(April2015),pages,100-107.
[2] VikasChaurasia, Saurabh Pal, BB Tiwari ,‖ Prediction of benign and malignant breast cancer using data mining techniques‖ Volume: 12 issue: 2, page(s): 119-126 . Issue published: June 1, 2018.
[3] M. Durairaj , K. Priya ,‖Breast Cancer Prediction Using Soft Computing Techniques – A Survey‖,International Journal of Computer Sciences and Engineering,Vol.-6, Issue-8, Aug 2018 E- ISSN: 2347-2693.
[4] Amjad Khan , Zahid Ahmed Ansari,‖ Early Detection of Breast Cancer using Soft Computing‖, IJSRD - International Journal for Scientific Research & Development| Vol. 5, Issue 10, 2017 | ISSN (online): 2321-0613.
[5] Ibrahim M. El-Hasnony, Hazem M. El-Bakry, Ahmed A. Saleh,‖ Classification of Breast Cancer Using Softcomputing Techniques‖ International Journal of Electronics and Information Engineering, Vol.4, No.1, PP.45-54, Mar.2016.
[6] SoumadipGhosh,SushantaBiswasandDebasreeChanda,―Breast Cancer Detection using a Neuro-fuzzy basedClassification Method‖ Indian Journal of Science and Technology, ISSN (Print): 0974- 6846, Vol 9(14), April 2016, pages, 1-15.
[7] N.S.Nithya,Dr.K.Duraiswamy,P.Gomathy,―ASurveyon Clustering Techniques in Medical Diagnosis‖ International Journal of Computer Science Trends and Technology (IJCST) Vol. 1 Issue2, Nov-Dec 2013.
[8] SL.Aarthy,S.Prabu.,―acomputerizedapproachonbreastcancer detection and classification‖ IIOAB Journal, ISSN: 0976-3104, Vol. 7/Issue 5/2016/157-169.
[9] Elouedi, H., Meliani, W., Elouedi, Z. and Amor, N.B., A hybrid approach based on decision trees and clustering for breast cancer classification. IEEE 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR), 2014, August, pp. 226-231.
[10] N.S.Nithiya,Dr.K.Duraiswamy,P.Gomathy ,‖A Survey On Clustering Techniques In Medical Diagnosis‖,International Journal Of Computer Science Trends And Technology (IJCST)-Volume 1 issue 2,Nov-Dec2013.
[11] J.Padmavathi,‖A Comparative study on Breast Cancer Prediction Using RBF and MLP‖,International Journal of Scientific & Engineering Research, Volume 2, Issue 1, January-2011 1 ISSN 2229-558.
[12] TubaKiyanandTulayYildirim,―BreastCancerDiagnosisUsing Statistical Neural Networks‖, Istanbul University, Journal of Electrical and Electronics Engineering, Year 2004, 4(2), 1149- 1153.
[13] Ms.SnehaBadrinathSanap,VijayL.Agrawal―DiagnosisofBreast Cancer using Multilayer Perceptron (MLP)‖,International Journal of Advance Foundation and Research in Computer (IJAFRC) Volume 3, Issue 4, April - 2016. ISSN : 2348 –4853.
[14] S.A Mojarad, S.S.Dlay& W.L. Woo and G.V Sherbet,‖ Breast cancer prediction and cross validation using multilayer perceptron neural networks‖, 2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP2010.4.760764.
[15] ShikhaAgrawal,JitendraAgrawal,‖Neural Network Techniques for Cancer Prediction: A Survey‖, 19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, https://doi.org/10.1016/j.procs.2015.08.234.
Citation
Jayshree Bhattacharya, Pranati Rakshit, Arindam Roy, Dharmpal Singh, Debolina Dalui, "Assessment of the Performance of MLP & Hierarchical Clustering Method in the Prediction of Breast Cancer", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.55-58, 2020.
Assessment of Exported Tea Quantity using Fuzzy Neural Model
Research Paper | Journal Paper
Vol.08 , Issue.01 , pp.59-63, Feb-2020
Abstract
In the field of prediction Assessment plays a major role. The prediction result becomes incorrect if a Assessment is not selected properly and the scope of future work becomes lost or unpredictable. Therefore an appropriate technique needs to be selected for the purpose of forecasting. There are lot of soft computing models which are being used in various application for the purpose of forecasting. The performance of fuzzy logic and Artificial Neural Network, in the field of soft computing, are being examined for the purpose of Assessment on the basis of average error. Here an effort is being used to select the proper soft computing technique to predict the futuristic information of quantity of exported tea to be exported in near future. Initially, the concept of Fuzzy Logic based on Fuzzy Membership Function has been applied and therefore after concept of Feed Forward Back propagation Neural Network of soft computing has been used to optimize the error.
Key-Words / Index Term
Fuzzy Logic, Artificial Neural Network, Feed Forward Back Propagation Neural Network, Soft Computing
References
[1] International Journal of Applied Evolutionary Computation (IJAEC), Vol. 8 No. 3 pp. 13-52, 2017 ACM Index.
[2] G . Purkait and D.P Singh, “An effort to optimize the error using statistical and soft computing methodologies" , Journal of Applied Computer Science & Artificial Intelligence Vol .1 No. 1, pp. 15-20, 2017.
31] D.P Singh, “ A Modified Bio Inspired BAT algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), Vol. 9 No. 1,pp. 60-77, 2018. Scopus Index
[4] D. P., J. P. Choudhury and M. De, “An Enhance DE algorithm for analysis in data set”, International Journal of Data Science (IJDS), 2016 (Accepted).
[5] Dharmpal Singh, Abhishek Banerjee, Gopal Purkait , “Assessment of Heart DiseaseTypes Using Clustering Techniques Under the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol.6 Issue 03 pp. 10-16, Print ISSN: 2231-2021 e-ISSN: 2231-0312 .
[6] D. P. Singh, S. Sahana, SK Saddam Ahmed , "A Comparative Study to Assess the Crohn’s Diseasetype using Statistical and Fuzzy Logic Methodology", International Journal of Computer Sciences and Engineering, Volume-04, Issue-06, Page No (41-46), Aug -2016, E-ISSN: 2347-2693
[7] D. P. Singh, J. P. Choudhury and M. De, “An effort to select a preferable meta heuristic model for knowledge discovery in Data mining”, International Journal of mataheuristics, Vol. 4 No. 1, pp.57-90, September, 2015. 1755-2184, ISSN print: 1755-2176 DBLP Index
[8] Sk. Saddam and D. P.Singh, “Genotype based classification of Crohn’s disease using various BPN training algorithms”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5 No. 2, pp.22-29, July, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[9] D. P. Singh, J. P. Choudhury and M. De, “A modified ACO for classification on different data set” International Journal of Computer Application, Vol.123, No. 6, pp-39-52, August 2015, ISSN 0975-8887..
[10] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Compare the Clustering Technique on Different Data Set Based On Distance Measure Function in the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5, No. 1, pp. 1-8,January, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[11] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Developing the Knowledge Base of Data mining with Association Rule Formation by Factor Analysis”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 3, No. 3, pp.18-23, October, 2013, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[12] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Developing the Knowledge Base in Data Mining by Factor Analysis and Soft Computing Methodology”, International Journal of Scientific & Engineering Research (IJSER), Vol. 4, No. 9, pp. 1912-1923, September, 2013, ISSN 2229-5518.
[13] D. P. Singh, J. P. Choudhury and M. De, “A comparative study on the performance of Fuzzy Logic, Bayesian Logic and neural network towards Decision Making” International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 4, No. 2, pp. 205-216, April, 2012. SSN online: 1755-8069
ISSN print: 1755-8050, Scopus Index
[14] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Knowledge Discovery in Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 2, No. 2, pp. 6-19, April, 2012.
[15] D. P. Singh, J. P. Choudhury and M. De, “ A Comparative Study on the performance of Soft Computing models in the domain of Data Mining,” International Journal of Advancements in Computer Science and Information Technology, Vol. 1, No. 1, pp. 35-49, September, 2011, ISSN 2277-9140.
[16] D. P. Singh, J. P. Choudhury and M. De, “Optimization of fruit quantity by different types of cluster technique”, Journal of Computer Sciences, Punjab, Vol. 9, No.1, pp. 17-28, June-July, 2011, ISSN 0973-4058.
[17] D. P. Singh, J. P. Choudhury and M. De, “Performance measurement of Soft Computing models based on
Residual Analysis”, International Journal for Applied Engineering and Research, Vol. 6, No. 5, Delhi, India, pp. 823-832, Jan-July, 2011, Print ISSN 0973-4562. Online ISSN 1087-1090. Scopus Index
[18] D. P. Singh, J. P. Choudhury and M. De, “Optimization of Fruit Quantity by comparison between Statistical Model and Fuzzy Logic by Bayesian Net work”, PCTE, Journal of Computer Sciences, Vol. 8, No.1, Punjab, pp. 91-95, June-July, 2010.
[19] D. P. Singh, J. P. Choudhury and M. De, “Prediction Based on Statistical and Fuzzy Logic Membership Function”, PCTE, Journal of Computer Sciences, Vol. 8, No. 1, Punjab, pp. 86-90 , June-July, 2010.
[20] D.P. Singh, J. P. Choudhury and M. De, “Performance Measurement of Neural Net work Model Considering Various Membership Functions under Fuzzy Logic”, International Journal of Computer and Engineering, Vol. 1, No. 2, pp. 1-5, 2010, ISSN-0976-9587.
[21] D. P. Singh, J. P. Choudhury, “Assessment of Exported Mango Quantity by Soft Computing Model”, International Journal of Information Technology and Knowledge Management, Kurukshetra University, Vol. 2, No. 2, pp. 393-395, June-July, 2009, ISSN : 0973-4414 .
Citation
Arindam Roy, Dharmpal Singh, Sudipta Sahana, Ira Nath, Pranati Rakshit, "Assessment of Exported Tea Quantity using Fuzzy Neural Model", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.59-63, 2020.
Statistical Approach to Estimate the Weather Prediction
Research Paper | Journal Paper
Vol.08 , Issue.01 , pp.64-69, Feb-2020
Abstract
The burgeoning research in the fields of statistical has given rise to numerous weather prediction models. But the problem of accurately predicting or forecasting the weather still persists. Numerical weather prediction is taking the existing numerical data on weather conditions and applying machine learning algorithms on it to forecast the weather. If the assessment of weather cannot be selected properly, the prediction information becomes incorrect and this will create lots of the problem in the real life. Therefore selection of an appropriate technique for the purpose of forecasting is needed. Here the effort is to select the soft computing technique properly for the prediction of the futuristic annual average Temperature of India. Initially, the concepts of least square base linear equation, exponential, asymptotic , curvilinear , logarithm have been applied to optimize the error and the concept of soft computing model will be used for the further enhance of the error. Moreover, the same concept has been applied on the tested data to select the optimality of the model predicted model.
Key-Words / Index Term
Soft Computing, Least Square Base Linear Equation, Weather prediction
References
[1] International Journal of Applied Evolutionary Computation (IJAEC), Vol. 8 No. 3 pp. 13-52, 2017 ACM Index.
[2] G . Purkait and D.P Singh, “An effort to optimize the error using statistical and soft computing methodologies" , Journal of Applied Computer Science & Artificial Intelligence Vol .1 No. 1, pp. 15-20, 2017.
31] D.P Singh, “ A Modified Bio Inspired BAT algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), Vol. 9 No. 1,pp. 60-77, 2018. Scopus Index
[4] D. P., J. P. Choudhury and M. De, “An Enhance DE algorithm for analysis in data set”, International Journal of Data Science (IJDS), 2016 (Accepted).
[5] Dharmpal Singh, Abhishek Banerjee, Gopal Purkait , “Assessment of Heart DiseaseTypes Using Clustering Techniques Under the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol.6 Issue 03 pp. 10-16, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[6] D. P. Singh, S. Sahana, SK Saddam Ahmed , "A Comparative Study to Assess the Crohn’s Diseasetype using Statistical and Fuzzy Logic Methodology", International Journal of Computer Sciences and Engineering, Volume-04, Issue-06, Page No (41-46), Aug -2016, E-ISSN: 2347-2693
[7] D. P. Singh, J. P. Choudhury and M. De, “An effort to select a preferable meta heuristic model for knowledge discovery in Data mining”, International Journal of mataheuristics, Vol. 4 No. 1, pp.57-90, September, 2015. 1755-2184, ISSN print: 1755-2176 DBLP Index
[8] Sk. Saddam and D. P.Singh, “Genotype based classification of Crohn’s disease using various BPN training algorithms”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5 No. 2, pp.22-29, July, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[9] D. P. Singh, J. P. Choudhury and M. De, “A modified ACO for classification on different data set” International Journal of Computer Application, Vol.123, No. 6, pp-39-52, August 2015, ISSN 0975-8887..
[10] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Compare the Clustering Technique on Different Data Set Based On Distance Measure Function in the Domain of Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 5, No. 1, pp. 1-8,January, 2015, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[11] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Developing the Knowledge Base of Data mining with Association Rule Formation by Factor Analysis”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 3, No. 3, pp.18-23, October, 2013, Print ISSN: 2231-2021 e-ISSN: 2231-0312.
[12] D. P. Singh, J. P. Choudhury and M. De, “An Effort to Developing the Knowledge Base in Data Mining by Factor Analysis and Soft Computing Methodology”, International Journal of Scientific & Engineering Research (IJSER), Vol. 4, No. 9, pp. 1912-1923, September, 2013, ISSN 2229-5518.
[13] D. P. Singh, J. P. Choudhury and M. De, “A comparative study on the performance of Fuzzy Logic, Bayesian Logic and neural network towards Decision Making” International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 4, No. 2, pp. 205-216, April, 2012. SSN online: 1755-8069 ISSN print: 1755-8050, Scopus Index
[14] D. P. Singh, J. P. Choudhury and M. De, “A Comparative Study to Select a Soft Computing Model for Knowledge Discovery in Data Mining”, International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 2, No. 2, pp. 6-19, April, 2012.
[15] D. P. Singh, J. P. Choudhury and M. De, “ A Comparative Study on the performance of Soft Computing models in the domain of Data Mining,” International Journal of Advancements in Computer Science and Information Technology, Vol. 1, No. 1, pp. 35-49, September, 2011, ISSN 2277-9140.
[16] D. P. Singh, J. P. Choudhury and M. De, “Optimization of fruit quantity by different types of cluster technique”, Journal of Computer Sciences, Punjab, Vol. 9, No.1, pp. 17-28, June-July, 2011, ISSN 0973-4058.
[17] D. P. Singh, J. P. Choudhury and M. De, “Performance measurement of Soft Computing models based on Residual Analysis”, International Journal for Applied Engineering and Research, Vol. 6, No. 5, Delhi, India, pp. 823-832, Jan-July, 2011, Print ISSN 0973-4562. Online ISSN 1087-1090. Scopus Index
[18] D. P. Singh, J. P. Choudhury and M. De, “Optimization of Fruit Quantity by comparison between Statistical Model and Fuzzy Logic by Bayesian Net work”, PCTE, Journal of Computer Sciences, Vol. 8, No.1, Punjab, pp. 91-95, June-July, 2010.
[19] D. P. Singh, J. P. Choudhury and M. De, “Prediction Based on Statistical and Fuzzy Logic Membership Function”, PCTE, Journal of Computer Sciences, Vol. 8, No. 1, Punjab, pp. 86-90 , June-July, 2010.
[20] D.P. Singh, J. P. Choudhury and M. De, “Performance Measurement of Neural Net work Model Considering Various Membership Functions under Fuzzy Logic”, International Journal of Computer and Engineering, Vol. 1, No. 2, pp. 1-5, 2010, ISSN-0976-9587.
[21] D. P. Singh, J. P. Choudhury, “Assessment of Exported Mango Quantity by Soft Computing Model”, International Journal of Information Technology and Knowledge Management, Kurukshetra University, Vol. 2, No. 2, pp. 393-395, June-July, 2009, ISSN : 0973-4414.
[22] A. Roy, S. Kundu , J. Bhattacharya , D. Singh , S. Sahana, Ira Nath, “Assessment of Exported Tea Quantity by Soft Computing Model”, International Journal of Computer Sciences and Engineering, Vol.-7, Special Issue-18, May 2019 E-ISSN: 2347-2693.
Citation
Arindam Roy, Dharmpal Singh, Sudipta Sahana, Ira Nath, "Statistical Approach to Estimate the Weather Prediction", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.64-69, 2020.