Collecting Channel State Information in Wi-Fi Access Points for IoT Forensics

by   Fabio Palmese, et al.

The Internet of Things (IoT) has boomed in recent years, with an ever-growing number of connected devices and a corresponding exponential increase in network traffic. As a result, IoT devices have become potential witnesses of the surrounding environment and people living in it, creating a vast new source of forensic evidence. To address this need, a new field called IoT Forensics has emerged. In this paper, we present CSI Sniffer, a tool that integrates the collection and management of Channel State Information (CSI) in Wi-Fi Access Points. CSI is a physical layer indicator that enables human sensing, including occupancy monitoring and activity recognition. After a description of the tool architecture and implementation, we demonstrate its capabilities through two application scenarios that use binary classification techniques to classify user behavior based on CSI features extracted from IoT traffic. Our results show that the proposed tool can enhance the capabilities of forensic investigations by providing additional sources of evidence. Wi-Fi Access Points integrated with CSI Sniffer can be used by ISP or network managers to facilitate the collection of information from IoT devices and the surrounding environment. We conclude the work by analyzing the storage requirements of CSI sample collection and discussing the impact of lossy compression techniques on classification performance.


page 3

page 4


Grant-Free Random Access of IoT devices in Massive MIMO with Partial CSI

The number of wireless devices is drastically increasing, resulting in m...

DeepMuD: Multi-user Detection for Uplink Grant-Free NOMA IoT Networks via Deep Learning

In this letter, we propose a deep learning-aided multi-user detection (D...

Cross-Technology Communications for Heterogeneous IoT Devices Through Artificial Doppler Shifts

Recent years have seen major innovations in developing energy-efficient ...

Massive Wireless Energy Transfer: Enabling Sustainable IoT Towards 6G Era

Recent advances on wireless energy transfer led to a promising solution ...

Self-Supervised Learning for WiFi CSI-Based Human Activity Recognition: A Systematic Study

Recently, with the advancement of the Internet of Things (IoT), WiFi CSI...

Rate-Splitting Multiple Access for Overloaded Cellular Internet of Things

In the near future, it is envisioned that cellular networks will have to...

Next2You: Robust Copresence Detection Based on Channel State Information

Context-based copresence detection schemes are a necessary prerequisite ...

Please sign up or login with your details

Forgot password? Click here to reset