DATA PERTURBATION FOR PRIVACY PRESERVATION IN DATA MINING

The extensive use of the Internet of Things (IoT) has risen up many concerns, including the protection of sensitive information. The data anonymization methods are utilized to protect the data against attacks. In this research work, a new anonymization method is introduced using perturbation to ensure security of the data. The performance of the anonymization method is evaluated in terms of privacy loss and utility and the experimental results prove the ef iciency of this method