B-Anonymization: Privacy beyond k-Anonymization and l-Diversity
Bhanu Prakash · International Journal for Research in Applied Science and Engineering Technology · 2018
Privacy is very important for both users and enterprises. Research is being done on various aspects of privacy preserving in data management systems. Many algorithms like k-anonymization, l-diversity and t-closeness have been proposed, but each of them has their own advantages and disadvantages. For example taking into account k-anonymization, different attacks such as Background Knowledge and Homogeneity attack can be done. Also lot of time is used in dividing the whole database into equivalence classes by comparing records. So, this algorithm is a slight improvement over k-anonymization in term of privacy and efficiency.