Time-based GNSS attack detection
- URL: http://arxiv.org/abs/2502.03868v2
- Date: Wed, 12 Feb 2025 07:18:09 GMT
- Title: Time-based GNSS attack detection
- Authors: Marco Spanghero, Panos Papadimitratos,
- Abstract summary: Cross-checking the provided time against alternative trusted time sources can lead to attack detection aiming at controlling the receiver time.
We implement adversaries spanning from simplistic spoofers to advanced ones synchronized with the constellation.
The method is largely agnostic to the satellite constellation and the attacker type, making time-based data validation of information compatible with existing receivers and readily deployable.
- Score: 0.0
- License:
- Abstract: To safeguard Civilian Global Navigation Satellite Systems (GNSS) external information available to the platform encompassing the GNSS receiver can be used to detect attacks. Cross-checking the GNSS-provided time against alternative multiple trusted time sources can lead to attack detection aiming at controlling the GNSS receiver time. Leveraging external, network-connected secure time providers and onboard clock references, we achieve detection even under fine-grained time attacks. We provide an extensive evaluation of our multi-layered defense against adversaries mounting attacks against the GNSS receiver along with controlling the network link. We implement adversaries spanning from simplistic spoofers to advanced ones synchronized with the GNSS constellation. We demonstrate attack detection is possible in all tested cases (sharp discontinuity, smooth take-over, and coordinated network manipulation) without changes to the structure of the GNSS receiver. Leveraging the diversity of the reference time sources, detection of take-over time push as low as 150us is possible. Smooth take-overs forcing variations as low as 30ns are also detected based on on-board precision oscillators. The method (and thus the evaluation) is largely agnostic to the satellite constellation and the attacker type, making time-based data validation of GNSS information compatible with existing receivers and readily deployable.
Related papers
- Time Synchronization of TESLA-enabled GNSS Receivers [0.8926368123237011]
We provide proof of security for each of our algorithms under a delay-capable adversary.
We discuss the implications of authentication schemes that use two simultaneous TESLA instances of different authentication cadences.
arXiv Detail & Related papers (2024-07-18T10:48:49Z) - DEMO: RTKiller -- manipulation of GNSS RTK rovers by reference base spoofing [0.0]
We show how manipulation of the Position Navigation and Timing solution at the reference station is reflected in the loss of baseline fix or degraded accuracy at the rover.
Attacking the reference stations can harm all receivers (rovers) that rely on the targeted reference station.
arXiv Detail & Related papers (2024-05-17T17:07:51Z) - Robust Collaborative Perception without External Localization and Clock Devices [52.32342059286222]
A consistent spatial-temporal coordination across multiple agents is fundamental for collaborative perception.
Traditional methods depend on external devices to provide localization and clock signals.
We propose a novel approach: aligning by recognizing the inherent geometric patterns within the perceptual data of various agents.
arXiv Detail & Related papers (2024-05-05T15:20:36Z) - Extending RAIM with a Gaussian Mixture of Opportunistic Information [1.9688858888666714]
Original receiver autonomous integrity monitoring (RAIM) was not designed for securing.
We extend RAIM by incorporating all opportunistic information, i.e., measurements from terrestrial infrastructures and onboard sensors.
The objective is to assess the likelihood of spoofing by analyzing locations derived from extended RAIM solutions.
arXiv Detail & Related papers (2024-02-05T19:03:18Z) - Location Estimation and Recovery using 5G Positioning: Thwarting GNSS Spoofing Attacks [2.8711436763354237]
cryptographic spoofers can prevent safe navigation and tracking of road users.
Spoofing can lead to loss of assets, inaccurate fare estimation, enforcing the wrong speed limit, miscalculated toll tax, passengers reaching an incorrect location.
We design the Location Estimation and Recovery(LER) systems to estimate the absolute position using the combination of correct and 5G positioning.
arXiv Detail & Related papers (2023-10-23T12:54:13Z) - Automated classification of pre-defined movement patterns: A comparison
between GNSS and UWB technology [55.41644538483948]
Real-time location systems (RTLS) allow for collecting data from human movement patterns.
The current study aims to design and evaluate an automated framework to classify human movement patterns in small areas.
arXiv Detail & Related papers (2023-03-10T14:46:42Z) - Learning Emergent Random Access Protocol for LEO Satellite Networks [51.575090080749554]
We propose a novel grant-free random access solution for LEO SAT networks, dubbed emergent random access channel protocol (eRACH)
eRACH is a model-free approach that emerges through interaction with the non-stationary network environment.
Compared to RACH, we show from various simulations that our proposed eRACH yields 54.6% higher average network throughput.
arXiv Detail & Related papers (2021-12-03T07:44:45Z) - Space-Time Graph Neural Networks [104.55175325870195]
We introduce space-time graph neural network (ST-GNN) to jointly process the underlying space-time topology of time-varying network data.
Our analysis shows that small variations in the network topology and time evolution of a system does not significantly affect the performance of ST-GNNs.
arXiv Detail & Related papers (2021-10-06T16:08:44Z) - TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack [46.79557381882643]
We present TANTRA, a novel end-to-end Timing-based Adversarial Network Traffic Reshaping Attack.
Our evasion attack utilizes a long short-term memory (LSTM) deep neural network (DNN) which is trained to learn the time differences between the target network's benign packets.
TANTRA achieves an average success rate of 99.99% in network intrusion detection system evasion.
arXiv Detail & Related papers (2021-03-10T19:03:38Z) - Prediction-Based GNSS Spoofing Attack Detection for Autonomous Vehicles [5.579370215490055]
We have developed a prediction-based spoofing attack detection strategy using the long short-term memory (LSTM) model.
Based on the predicted distance traveled between the current location and the immediate future location, a threshold value is established.
Our analysis revealed that the prediction-based spoofed attack detection strategy can successfully detect the attack in real-time.
arXiv Detail & Related papers (2020-10-16T18:26:59Z) - Defending Water Treatment Networks: Exploiting Spatio-temporal Effects
for Cyber Attack Detection [46.67179436529369]
Water Treatment Networks (WTNs) are critical infrastructures for local communities and public health, WTNs are vulnerable to cyber attacks.
We propose a structured anomaly detection framework to defend WTNs by modeling thetemporal characteristics of cyber attacks in WTNs.
arXiv Detail & Related papers (2020-08-26T15:56:55Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.