# Privacy Preserving Utility Mining: A Survey

arXiv: https://arxiv.org/abs/1811.07389 · HTML: https://mlsanity.com/paper/1811.07389/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Nov 2018.

## Built on by (most cited first, 8 of 8)

- [Large Language Models in Education: Vision and Opportunities](https://mlsanity.com/paper/2311.13160/) (2023)
- [Model-as-a-Service (MaaS): A Survey](https://mlsanity.com/paper/2311.05804/) (2023)
- [Anomaly Rule Detection in Sequence Data](https://mlsanity.com/paper/2111.15026/) (2021)
- [TargetUM: Targeted High-Utility Itemset Querying](https://mlsanity.com/paper/2111.00309/) (2021)
- [Towards Revenue Maximization with Popular and Profitable Products](https://mlsanity.com/paper/2202.13041/) (2022)
- [Smart System: Joint Utility and Frequency for Pattern Classification](https://mlsanity.com/paper/2206.04269/) (2022)
- [A Generic Algorithm for Top-K On-Shelf Utility Mining](https://mlsanity.com/paper/2208.14230/) (2022)
- [HUSP-SP: Faster Utility Mining on Sequence Data](https://mlsanity.com/paper/2212.14255/) (2022)

## Abstract (arXiv)

In big data era, the collected data usually contains rich information and hidden knowledge. Utility-oriented pattern mining and analytics have shown a powerful ability to explore these ubiquitous data, which may be collected from various fields and applications, such as market basket analysis, retail, click-stream analysis, medical analysis, and bioinformatics. However, analysis of these data with sensitive private information raises privacy concerns. To achieve better trade-off between utility maximizing and privacy preserving, Privacy-Preserving Utility Mining (PPUM) has become a critical issue in recent years. In this paper, we provide a comprehensive overview of PPUM. We first present the background of utility mining, privacy-preserving data mining and PPUM, then introduce the related preliminaries and problem formulation of PPUM, as well as some key evaluation criteria for PPUM. In particular, we present and discuss the current state-of-the-art PPUM algorithms, as well as their advantages and deficiencies in detail. Finally, we highlight and discuss some technical challenges and open directions for future research on PPUM.