WITHDRAWN: Security protocol of sensitive high utility itemset hiding in shared IoT environments

Abstract

Listen

Translate article

Abstract As Internet Technology (IT) rapidly grows, it is necessary to protect private and confidential information of collected data from both smart and Internet of Things (IoT) devices. It becomes a necessity to protect and hide confidential or private information for data sharing or publishing between collaborators and partners. The concept of Privacy-Preserving Data Mining, known as PPDM, is created to clean the database for hiding sensitive information. However, it applies only to binary databases. To handle Privacy-Preserving Utility Mining, known as PPUM, we present a Maximum Sensitive Utility-Maximum Sensitive conflIct algorithm, known as MSU-MSI, to find conflicting items within sensitive high-utility itemsets for sanitization of data. Transactions with sensitive high-utility itemsets are first projected for the sanitization process. Next, the number of conflicting items within the itemsets is calculated, and the designed progress is used to reduce the quantity value of processed items for sanitization. In our experimental results, the designed algorithm is compared with the standard algorithms like HHUIF, MSICF, and the state-of-the-art MSU-MAX and MSU-MIN approaches. Finally, the proposed MSU-MSI is shown to achieve better performance in terms of missing cost, especially in extreme datasets (very dense or very sparse), a true testament to the process. Furthermore, the designed MSU-MSI achieved an excellent performance in terms of database structure similarity and database utility similarity with a very slight difference compared to the previously achieved top results.