Indexing
All Issues
Submission
Author Guidelines
Reviewers
Editorial Members
Publication Fee
Vol.2 , No. 1, Publication Date: Mar. 11, 2015, Page: 1-6
 cancer will became leading cause of woman death of the world wide. Breast cancer has become the most hazardous type of cancer among woman in the world. Early detection of breast cancer is essential in reducing life losses. In this paper mining rules to mine the attributes relationship. The support and confidence value are used to estimated from all item set. Minimum support and confidence value are used to predict rule from the list datasets. Our proposed work is applicable where the numbers of sites are greater than two and each site want to calculate the global rule and global confidence from the database without disclosing their private information to other sites presents in the global environments. Our proposed algorithm Double Hash Based Cryptography Algorithm (DHBCA) to provide the highest privacy in the breast cancer database and also zero percent of data leakage.&picture=http://www.aascit.org/aascit/decorators/img/journal/912.jpg)
| [1] | Raghvendra Kumar, Faculty of Engineering Technology, Jodhpur National University, Jodhpur, Rajsthan, India. |
| [2] | Prasant Kumar Pattnaik, School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. |
| [3] | Yogesh Sharma, Faculty of Engineering Technology, Jodhpur National University, Jodhpur, Rajsthan, India. |
According to the world health organization (WHO) cancer will became leading cause of woman death of the world wide. Breast cancer has become the most hazardous type of cancer among woman in the world. Early detection of breast cancer is essential in reducing life losses. In this paper mining rules to mine the attributes relationship. The support and confidence value are used to estimated from all item set. Minimum support and confidence value are used to predict rule from the list datasets. Our proposed work is applicable where the numbers of sites are greater than two and each site want to calculate the global rule and global confidence from the database without disclosing their private information to other sites presents in the global environments. Our proposed algorithm Double Hash Based Cryptography Algorithm (DHBCA) to provide the highest privacy in the breast cancer database and also zero percent of data leakage.
Keywords
Breast Cancer Database, Distributed Database, Association Rule Mining, Cryptography Algorithm, Privacy
Reference
| [01] | American Cancer Society. Breast Cancer Facts & Figures 2005-2006. Atlanta: American Cancer Society, Inc. (http://www.cancer.org/). |
| [02] | A.Bellachia and E.Guvan,“Predicting breast cancer survivability using data mining techniques”, Scientific Data Mining Workshop, in conjunction with the 2006 SIAM Conference on Data Mining, 2006. |
| [03] | A. Endo, T. Shibata and H. Tanaka (2008), Comparison of seven algorithms to predict breast cancer survival, Biomedical Soft Computing and Human Sciences, vol.13, pp.11-16. |
| [04] | Breast Cancer Wisconsin Data [online]. Available: http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancerwisconsin/ breast-cancer-wisconsin.data. |
| [05] | Brenner, H., Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. Lancet. 360:1131–1135, 2002. |
| [06] | D. Delen, G. Walker and A. Kadam (2005), Predicting breast cancer survivability: a comparison of three data mining methods, Artificial Intelligence in Medicine, vol.34, pp.113-127. |
| [07] | Ian H. Witten and Eibe Frank. Data Mining: Practical machine learning tools and techniques, 2nd Edition. San Fransisco: Morgan Kaufmann; 2005. |
| [08] | J. Han and M. Kamber, Data Mining-Concepts and Technique (The Morgan Kaufmann Series in Data Management Systems), 2nd ed. San Mateo, CA: Morgan Kaufmann, 2006. |
| [09] | Mitchell, T. M., Machine Learning, McGraw-Hill Science/Engineering/Math, 1997 |
| [10] | P.-N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining. Reading, MA: Addison-Wesley, 2005. |
| [11] | Razavi, A. R., Gill, H., Ahlfeldt, H., and Shahsavar, N., Predicting metastasis in breast cancer: comparing a decision tree with domain experts. J. Med. Syst. 31:263–273, 2007. |
| [12] | S.B.Kotsiantis and P.E.Pintelas,”Combining Bagging and Boosting”, International Journal of Information and Mathematical Sciences, 1:4 2005. |
