Dr.-Ing. Daniel Steinmetzer

Offered Theses Topics

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  2018 Completed

Learning the Beams: Efficient Millimeter-Wave Beam-Steering Techniques

Motivation Beam-steering is the backbone of millimeter-wave (mm-wave) networks and key to achieve data-rates of multiple gigabit per second. Nodes must steer their antennas so that they maximize the signal gain towards the intended communication partner. The state-of-the-art to find the best antenna configuration is to probe all possible antenna configurations. This process caused high overhead, especially in case of mobility when parameters must be adjusted continuously. Goal In this thesis, you apply machine learning techniques to find the antenna parameters most suitable for probing and select the optimal configuration with low overhead. Implementation and evaluation in this thesis, should be performed by means of our mm-wave testbed platform with off-the-shelf IEEE 802.11ad devices. Experience with Linux, wireless network configuration, proper tools, and scripting languages is highly recommended.

  2018 Completed

Learning the Beams: Applying Evolution Algorithms for Optimized IEEE 802.11 ad Beamtraining

  2018 Completed

Practical Low-Layer Attacks on IEEE802.11ad by Modified WiFi Firmware

Motivation Millimeter-Wave (mm-wave) communication systems such as IEEE 802.11ad use directional beams that need to be trained prior to establishing a high-throughput connection. Such beam training protocols–the backbone of mm-wave communications–have a high impacts of the security of performance. Jamming or manipulating the frames associated with the beam steering might prevent a connection from being established or steer the beam for an adversary’s benefit. We already obtained access to a WiFi chip of state-of-the-art routers at firmware level. Goal A bachelor or master thesis is this area might extend our current framework and integrate, for example, packet injection or jamming to launch and evaluate the aforementioned attacks. Students should not be afraid of analyzing binary data and assembly instructions. Experience with IDA Pro is recommended.

  2018 Completed

60 Ghz Channel Models: From Theory to Practice (and Back Again)

Motivation The channel characteristics of millimeter-wave communication systems at 60 GHz differ those in lower frequency bands and require a fundamental rethinking of network design. To investigate such aspects of network performance, we developed a raytracing based simulation framework to predict the signal quality in arbitrary environments. However, the internals in the simulation are based on theoretical considerations and models. So far, simulation results have not been compared to realistic measurements. Goal In this thesis, your task is to extend our simulation framework [1] in MATLAB and/or Python and compare results with realistic measurements performed with common IEEE 802.11ad router hardware. We expect that impairments due to cheap antenna and RF circuit design lead to divergences from simulation. Can you adapt the simulation to provide more realistic outcomes? [1] mmTrace: ray-tracing based millimeter-wave propagation simulation

  2018 Completed

Using Physical Unclonable Functions (PUFs) for Data-Link Layer Authenticity Verification to Mitigate Attacks on IEEE 802.11ad Beam Training

  2017 Completed

Investigating practical man-in-the-middle network attacks on IEEE 802.11 ad

  2016 Completed

Unified Multi-modal Secure Device Pairing for Infrastructure and Ad-hoc Networks Bachelor Thesis

Motivation Todays technologies heavily rely on wireless communications. Our mobile devices connect to infrastructure devices such as wireless routers, perform ad-hoc connections among each other and connect to peripheral devices such as smart watches, fitness tracker and headsets. However, since security is essential in most application scenarios, authentication is a big challenge. To join a wireless network pre-shared credentials are required. Pairing in proximity via bluetooth requires the same pin to be entered on both devices. This proceeding is inconvenient and differs for different kinds of devices. Although, user-friendly and secure pairing mechanisms utilizing multi-modal technologies are proposed, no unified solution exists, yet. Goal In this thesis you elaborate different kind of pairing mechanism and analyze their security regarding various attacks. You design a unified multi-modal pairing protocol and implement a prototype on Android. Your protocol combines pairing strategies over different communication technologies (e.g. WiFi, Bluetooth, NFC, sound, light) and selects a suitable subset matching the devices capabilities. Since some strategies are easier to intercept than others, your protocol attests the paring procedure for retrospective trust estimation in application context. With your proposal we show that a unified multi-modal paring is feasible for both infrastructure and ad-hoc networks with flexible security requirements.

  2016 Completed

Unified Multi-Modal Device Pairing in Infrastructure and Ad-hoc networks


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Performance and Security Enhancements in Practical Millimeter-Wave Communication Systems

TPy: A Lightweight Framework for Agile Distributed Network Experiments

Adaptive Codebook Optimization for Beam-Training on Off-The-Shelf IEEE 802.11ad Devices

Fast and Infuriating: Performance and Pitfalls of 60 GHz WLANs Based on Consumer-Grade Hardware

Beam-Stealing: Intercepting the Sector Sweep to Launch Man-in-the-Middle Attacks on Wireless IEEE 802.11ad Networks

Indoor Localization Using Commercial Off-The-Shelf 60 GHz Access Points

TPy: A Lightweight Framework for Agile Distributed Network Experiments

Compressive Millimeter-Wave Sector Selection in Off-the-Shelf IEEE 802.11ad Devices

Mitigating Lateral Interference: Adaptive Beam Switching for Robust Millimeter-Wave Networks

Survey and Systematization of Secure Device Pairing

Massive reactive smartphone-based jamming using arbitrary waveforms and adaptive power control

Far Away and Yet Nearby - A Framework for Practical Distance Fraud on Proximity Services for Mobile Devices (Demo)

Lockpicking Physical Layer Key Exchange: Weak Adversary Models Invite the Thief