arXiv subjects

Bernhard Etzlinger

Publications and source records attributed to Bernhard Etzlinger.

8 recordsLinked to original sources

arXiv2026

Secure Wi-Fi Ranging Today: Security and Adoption of IEEE 802.11az/bk

Ranging and localisation have become critical for many applications and services. The Wi-Fi (IEEE 802.11) standard is a natural candidate for providing these functions across diverse environments, given its widespread deployment. The IEEE 802.11az amendment, finalised in 2023, introduces "Next Generation Positioning" mechanisms to secure and harden the existing insecure Wi-Fi Fine Timing Measurement (FTM) ranging solution. Moreover, the recent IEEE 802.11bk amendment increases the available bandwidth with the goal of approaching the centimetre-level ranging accuracy of ultra-wideband (UWB) systems. This paper examines to what extent these promises hold from a security and deployability perspective. We analyse the core mechanisms of secure Wi-Fi ranging as defined in IEEE 802.11az and IEEE 802.11bk at both the logical and physical layers, combining standards analysis with simulations and measurements on commercial and development hardware. At the logical layer, we show how common deployment choices can result in unauthenticated ranging, downgrade attacks, and simple denial-of-service attacks, making it difficult to securely realise many high-stakes use cases. At the physical layer, we study the predictability of secure ranging waveforms, the security impact of symbol repetition, and how waveform design choices affect compliance with spectral masks under realistic RF behaviour. Our results show that secure Wi-Fi ranging is highly sensitive to configuration choices and is non-trivial to implement on existing hardware. This is also evidenced by the currently limited support for secure Wi-Fi ranging in commodity devices. This paper provides practical guidelines for using secure FTM safely and recommendations to vendors and standardisation bodies to improve its robustness and deployability.

cs.CR↗

arXiv2024

Trustworthiness for an Ultra-Wideband Localization Service

Trustworthiness assessment is an essential step to assure that interdependent systems perform critical functions as anticipated, even under adverse conditions. In this paper, a holistic trustworthiness assessment framework for ultra-wideband self-localization is proposed, including attributes of reliability, security, privacy, and resilience. Our goal is to provide guidance for evaluating a system's trustworthiness based on objective evidence, so-called trustworthiness indicators. These indicators are carefully selected through the threat analysis of the particular system. Our approach guarantees that the resulting trustworthiness indicators correspond to chosen real-world threats. Moreover, experimental evaluations are conducted to demonstrate the effectiveness of the proposed method. While the framework is tailored for this specific use case, the process itself serves as a versatile template, which can be used in other applications in the domains of the Internet of Things or cyber-physical systems.

eess.SP↗

arXiv2021

Distance Estimation for BLE-based Contact Tracing -- A Measurement Study

Mobile contact tracing apps are -- in principle -- a perfect aid to condemn the human-to-human spread of an infectious disease such as COVID-19 due to the wide use of smartphones worldwide. Yet, the unknown accuracy of contact estimation by wireless technologies hinders the broader use. We address this challenge by conducting a measurement study with a custom testbed to show the capabilities and limitations of Bluetooth Low Energy (BLE) in different scenarios. Distance estimation is based on interpreting the signal pathloss with a basic linear and a logarithmic model. Further, we compare our results with accurate ultra-wideband (UWB) distance measurements. While the results indicate that distance estimation by BLE is not accurate enough, a contact detector can detect contacts below 2.5 m with a true positive rate of 0.65 for the logarithmic and of 0.54 for the linear model. Further, the measurements reveal that multi-path signal propagation reduces the effect of body shielding and thus increases detection accuracy in indoor scenarios.

cs.IR↗

arXiv2021

Using Channel State Information for Physical Tamper Attack Detection in OFDM Systems: A Deep Learning Approach

This letter proposes a deep learning approach to detect a change in the antenna orientation of transmitter or receiver as a physical tamper attack in OFDM systems using channel state information. We treat the physical tamper attack problem as a semi-supervised anomaly detection problem and utilize a deep convolutional autoencoder (DCAE) to tackle it. The past observations of the estimated channel state information (CSI) are used to train the DCAE. Then, a post-processing is deployed on the trained DCAE output to perform the physical tamper detection. Our experimental results show that the proposed approach, deployed in an office and a hall environment, is able to detect on average 99.6% of tamper events (TPR = 99.6%) while creating zero false alarms (FPR = 0%).

eess.SP↗

arXiv2018

SecSens: Secure State Estimation with Application to Localization and Time Synchronization

Research evidence in Cyber-Physical Systems (CPS) shows that the introduced tight coupling of information technology with physical sensing and actuation leads to more vulnerability and security weaknesses. But, the traditional security protection mechanisms of CPS focus on data encryption while neglecting the sensors which are vulnerable to attacks in the physical domain. Accordingly, researchers attach utmost importance to the problem of state estimation in the presence of sensor attacks. In this work, we present SecSens, a novel approach for secure nonlinear state estimation in the presence of modeling and measurement noise. SecSens consists of two independent algorithms, namely, SecEKF and SecOPT, which are based on Extended Kalman Filter and Maximum Likelihood Estimation, respectively. We adopt a holistic approach to introduce security awareness among state estimation algorithms without requiring specialized hardware, or cryptographic techniques. We apply SecSens to securely localize and time synchronize networked mobile devices. SecSens provides good performance at run-time several order of magnitude faster than the state of art solutions under the presence of powerful attacks. Our algorithms are evaluated on a testbed with static nodes and a mobile quadrotor all equipped with commercial ultra-wide band wireless devices.

cs.CR↗

arXiv2016

Cooperative Simultaneous Localization and Synchronization in Mobile Agent Networks

Cooperative localization in agent networks based on interagent time-of-flight measurements is closely related to synchronization. To leverage this relation, we propose a Bayesian factor graph framework for cooperative simultaneous localization and synchronization (CoSLAS). This framework is suited to mobile agents and time-varying local clock parameters. Building on the CoSLAS factor graph, we develop a distributed (decentralized) belief propagation algorithm for CoSLAS in the practically important case of an affine clock model and asymmetric time stamping. Our algorithm allows for real-time operation and is suitable for a time-varying network connectivity. To achieve high accuracy at reduced complexity and communication cost, the algorithm combines particle implementations with parametric message representations and takes advantage of a conditional independence property. Simulation results demonstrate the good performance of the proposed algorithm in a challenging scenario with time-varying network connectivity.

cs.DC↗

arXiv2016

Cooperative Joint Localization and Clock Synchronization Based on Gaussian Message Passing in Asynchronous Wireless Networks

Localization and synchronization are very important in many wireless applications such as monitoring and vehicle tracking. Utilizing the same time of arrival (TOA) measurements for simultaneous localization and synchronization is challenging. In this paper, we present a factor graph (FG) representation of the joint localization and time synchronization problem based on TOA measurements, in which the non-line-of-sight measurements are also taken into consideration. On this FG, belief propagation (BP) message passing and variational message passing (VMP) are applied to derive two fully distributed cooperative algorithms with low computational requirements. Due to the nonlinearity in the observation function, it is intractable to compute the messages in closed form and most existing solutions rely on Monte Carlo methods, e.g., particle filtering. We linearize a specific nonlinear term in the expressions of messages, which enables us to use a Gaussian representation for all messages. Accordingly, only the mean and variance have to be updated and transmitted between neighboring nodes, which significantly reduces the communication overhead and computational complexity. A message passing schedule scheme is proposed to trade off between estimation performance and communication overhead. Simulation results show that the proposed algorithms perform very close to particle-based methods with much lower complexity especially in densely connected networks.

cs.IT↗

arXiv2013

Cooperative Synchronization in Wireless Networks

Synchronization is a key functionality in wireless network, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two message passing methods (belief propagation and mean field), analyze their convergence behavior, and perform a qualitative and quantitative comparison with a number of competing algorithms. We also show that both methods can be applied in networks with and without master nodes. Our performance results are complemented by, and compared with, the relevant Bayesian Cramér-Rao bounds.

cs.DC↗