Building upon our previous work in a research project on identifying industrial components and software, this thesis extends the research into the domain of networked environments, focusing on the automatic discovery and identification of WiFi-enabled devices. Modern production and operational environments are increasingly relying on wireless communication, introducing new challenges in network security, asset management, and risk assessment. While many industrial and commercial settings still use legacy devices without proper security mechanisms, the transition toward fully connected infrastructures demands robust monitoring and identification techniques.
By contributing to the development of advanced methods for identifying WiFi devices in a network, you will help enhance network visibility, improve security measures, and enable better management of connected assets.
Student Target Groups:
- Students of ICE/Telematics;
- Students of Computer Science;
- Students of Software Engineering.
Thesis Type:
- Bachelor Thesis / Master Project / Master Thesis
Goal and Tasks:
The goal of this thesis is to explore techniques for automatically identifying WiFi devices within a network using passive and active fingerprinting approaches. By analyzing characteristics such as signal patterns, packet structures, and communication behaviors, it is possible to infer device types, manufacturers, and even potential security vulnerabilities.
- Conduct a thorough literature review on WiFi device identification techniques;
- Investigate passive fingerprinting methods for identifying devices based on observable network characteristics;
- Explore active identification techniques involving controlled network interactions while minimizing intrusiveness;
- Develop and implement a prototype tool for automated WiFi device discovery and classification;
- Design and conduct experiments to validate the accuracy and effectiveness of the proposed methods;
- Summarize findings in a written thesis and present the results in an oral defense.
Recommended Prior Knowledge:
- Programming skills in C, C++;
- Prior experience with network architectures;
- Interest in the topic.
Start:
Contact: