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Title |
A Knn Based Multiple Forms of Attack Prevention Algorithm for Non-Numerical Big Data in Medical Domain |
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Author |
Mahwish Abid, Muhammad Sheraz Arshad Malik, Muhammad Usman, Muhammad Mashhood ul Hasan, Zainab Khalid |
| Citation |
Vol. 18 No. 12 pp. 138-144 |
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Abstract |
The data which is in the large quantity and complicated to a certain level that the traditional data processing tools are unsuccessful to be applied on them is known as big data. Big data offers assistance in many fields such as IT, healthcare, customer care, e-commerce and many more. But it provide major benefits in the field of healthcare. But with the advancement of technology and internet, big healthcare data privacy has become a major concern these days. Intruder can perform numerous attacks or get some sensitive information about the patient which can be misused or mishandled. Various techniques and methodologies including anonymization has been proposed for big healthcare data security. But still data suffers from various attacks. While on the other hand such techniques only works for numerical data. Therefore, to handle the background knowledge and homogeneity attack an algorithm is proposed to handle the non-numerical data in this research. Results were calculate with the help of a tool where success rates are found and data re-identification rates are seen. |
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Keywords |
K-anonymization, background knowledge attack, homogeneity attack, generalization, microaggregation |
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