# Analyzing Consumer IoT Traffic from Security and Privacy Perspectives: a Comprehensive Survey

arXiv: https://arxiv.org/abs/2403.16149 · HTML: https://mlsanity.com/paper/2403.16149/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 40 of its 211 references that are in the map.
- First posted on arXiv 24 Mar 2024.

## Builds on (most cited first, 30 of 40)

- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [Challenges and Applications of Large Language Models](https://mlsanity.com/paper/2307.10169/) (2023)
- [A Critical Review of Recurrent Neural Networks for Sequence Learning](https://mlsanity.com/paper/1506.00019/) (2015)
- [Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset](https://mlsanity.com/paper/1811.00701/) (2018)
- [D"IoT: A Federated Self-learning Anomaly Detection System for IoT](https://mlsanity.com/paper/1804.07474/) (2018)
- [N-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders](https://mlsanity.com/paper/1805.03409/) (2018)
- [IoT Sentinel: Automated Device-Type Identification for Security Enforcement in IoT](https://mlsanity.com/paper/1611.04880/) (2016)
- [Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion Detectors](https://mlsanity.com/paper/2005.07519/) (2020)
- [New Directions in Automated Traffic Analysis](https://mlsanity.com/paper/2008.02695/) (2020)
- [A Survey on Device Behavior Fingerprinting: Data Sources, Techniques, Application Scenarios, and Datasets](https://mlsanity.com/paper/2008.03343/) (2020)
- [Peek-a-Boo: I see your smart home activities, even encrypted!](https://mlsanity.com/paper/1808.02741/) (2018)
- [Tracking, Profiling, and Ad Targeting in the Alexa Echo Smart Speaker Ecosystem](https://mlsanity.com/paper/2204.10920/) (2022)
- [A Smart Home is No Castle: Privacy Vulnerabilities of Encrypted IoT Traffic](https://mlsanity.com/paper/1705.06805/) (2017)
- [Your Smart Home Can't Keep a Secret: Towards Automated Fingerprinting of IoT Traffic with Neural Networks](https://mlsanity.com/paper/1909.00104/) (2019)
- [A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild](https://mlsanity.com/paper/2009.01880/) (2020)
- [Timely Detection and Mitigation of Stealthy DDoS Attacks via IoT Networks](https://mlsanity.com/paper/2006.08064/) (2020)
- [Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic](https://mlsanity.com/paper/2105.05162/) (2021)
- [Identification of Wearable Devices with Bluetooth](https://mlsanity.com/paper/1809.10387/) (2018)
- [IoTGaze: IoT Security Enforcement via Wireless Context Analysis](https://mlsanity.com/paper/2006.15827/) (2020)
- [IoTDevID: A Behavior-Based Device Identification Method for the IoT](https://mlsanity.com/paper/2102.08866/) (2021)
- [Protected or Porous: A Comparative Analysis of Threat Detection Capability of IoT Safeguards](https://mlsanity.com/paper/2304.03045/) (2023)
- [Keeping the Smart Home Private with Smart(er) IoT Traffic Shaping](https://mlsanity.com/paper/1812.00955/) (2018)
- [IoT Inspector: Crowdsourcing Labeled Network Traffic from Smart Home Devices at Scale](https://mlsanity.com/paper/1909.09848/) (2019)
- [Traffic Refinery: Cost-Aware Data Representation for Machine Learning on Network Traffic](https://mlsanity.com/paper/2010.14605/) (2020)
- [IoTGAN: GAN Powered Camouflage Against Machine Learning Based IoT Device Identification](https://mlsanity.com/paper/2201.03281/) (2022)
- [Spying on the Smart Home: Privacy Attacks and Defenses on Encrypted IoT Traffic](https://mlsanity.com/paper/1708.05044/) (2017)
- [Security and Privacy Analyses of Internet of Things Children's Toys](https://mlsanity.com/paper/1805.02751/) (2018)
- [Securing Fog-to-Things Environment Using Intrusion Detection System Based On Ensemble Learning](https://mlsanity.com/paper/1901.10933/) (2019)
- [IoT or NoT: Identifying IoT Devices in a ShortTime Scale](https://mlsanity.com/paper/1910.05647/) (2019)
- [Botnet Detection Using Recurrent Variational Autoencoder](https://mlsanity.com/paper/2004.00234/) (2020)

## Abstract (arXiv)

The Consumer Internet of Things (CIoT), a notable segment within the IoT domain, involves the integration of IoT technology into consumer electronics and devices, such as smart homes and smart wearables. Compared to traditional IoT fields, CIoT differs notably in target users, product types, and design approaches. While offering convenience to users, it also raises new security and privacy concerns. Network traffic analysis, a widely used technique in the security community, has been extensively applied to investigate these concerns about CIoT. Compared to traditional network traffic analysis in fields like mobile apps and websites, CIoT introduces unique characteristics that pose new challenges and research opportunities. Researchers have made significant contributions in this area. To aid researchers in understanding the application of traffic analysis tools for assessing CIoT security and privacy risks, this survey reviews 310 publications on traffic analysis within the CIoT security and privacy domain from January 2018 to June 2024, focusing on three research questions. Our work: 1) outlines the CIoT traffic analysis process and highlights its differences from general network traffic analysis. 2) summarizes and classifies existing research into four categories according to its application objectives: device fingerprinting, user activity inference, malicious traffic detection, and measurement. 3) explores emerging challenges and potential future research directions based on each step of the CIoT traffic analysis process. This will provide new insights to the community and guide the industry towards safer product designs.