# Data Privacy Preservation on the Internet of Things

arXiv: https://arxiv.org/abs/2304.00258 · HTML: https://mlsanity.com/paper/2304.00258/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 55 references that are in the map.
- First posted on arXiv 1 Apr 2023.

## Builds on (most cited first, 10 of 10)

- [Deep Learning with Differential Privacy](https://mlsanity.com/paper/1607.00133/) (2016)
- [Membership Inference Attacks against Machine Learning Models](https://mlsanity.com/paper/1610.05820/) (2016)
- [Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning](https://mlsanity.com/paper/1702.07464/) (2017)
- [A Survey of Privacy Attacks in Machine Learning](https://mlsanity.com/paper/2007.07646/) (2020)
- [DeepSecure: Scalable Provably-Secure Deep Learning](https://mlsanity.com/paper/1705.08963/) (2017)
- [A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics](https://mlsanity.com/paper/1703.02952/) (2017)
- [Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud](https://mlsanity.com/paper/1809.03428/) (2018)
- [Privacy-preserving Machine Learning through Data Obfuscation](https://mlsanity.com/paper/1807.01860/) (2018)
- [On Lightweight Privacy-Preserving Collaborative Learning for Internet of Things by Independent Random Projections](https://mlsanity.com/paper/2012.07626/) (2020)
- [Privacy-Preserving Personal Model Training](https://mlsanity.com/paper/1703.00380/) (2017)

## Abstract (arXiv)

Recent developments in hardware and information technology have enabled the emergence of billions of connected, intelligent devices around the world exchanging information with minimal human involvement. This paradigm, known as the Internet of Things (IoT) is progressing quickly with an estimated 27 billion devices by 2025. This growth in the number of IoT devices and successful IoT services has generated a tremendous amount of data. However, this humongous volume of data poses growing concerns for user privacy. This introductory chapter has presented a brief survey of some of the existing data privacy-preservation schemes proposed by researchers in the field of the Internet of Things.