160 research outputs found
Performance Bounds for Finite Moving Average Change Detection: Application to Global Navigation Satellite Systems
Due to the widespread deployment of Global Navigation Satellite Systems
(GNSSs) for critical road or urban applications, one of the major challenges to
be solved is the provision of integrity to terrestrial environments, so that
GNSS may be safety used in these applications. To do so, the integrity of the
received GNSS signal must be analyzed in order to detect some local effect
disturbing the received signal. This is desirable because the presence of some
local effect may cause large position errors, and hence compromise the signal
integrity. Moreover, the detection of such disturbing effects must be done
before some pre-established delay. This kind of detection lies within the field
of transient change detection. In this work, a finite moving average stopping
time is proposed in order to approach the signal integrity problem with a
transient change detection framework. The statistical performance of this
stopping time is investigated and compared, in the context of multipath
detection, to other different methods available in the literature. Numerical
results are presented in order to assess their performance.Comment: 12 pages, 2 figures, transaction paper, IEEE Transaction on Signal
Processing, 201
On the Use of a Feedback Tracking Architecture for Satellite Navigation Spoofing Detection
In this paper, the Extended Coupled Amplitude Delay Lock Loop (ECADLL) architecture, previously introduced as a solution able to deal with a multipath environment, is revisited and
improved to tailor it to spoofing detection purposes. Exploiting a properly-defined decision algorithm, the architecture is able to effectively detect a spoofer attack, as well as distinguish it from other kinds of interference events. The new algorithm is used to classify them according to their characteristics. We also introduce the use of a ratio metric detector in order to reduce the detection latency and the computational load of the architecture
Security Evaluation of GNSS Signal Quality Monitoring Techniques against Optimal Spoofing Attacks
GNSSs have a significant impact on everyday life and, therefore, the are increasingly becoming an attractive target for illicit exploitation. As such, anti-spoofing algorithms have become an relevant research topic within the GNSS discipline. This Thesis provides a review of recent research in the field of GNSS spoofing/anti-spoofing, designs a method to generate an energy optimal spoofing signal and evaluates the performance of the anti-spoofing signal quality monitoring techniques against it
Signal processing techniques for GNSS anti-spoofing algorithms
The Global Navigation Satellite Systems (GNSS) usage is growing at a very high
rate, and more applications are relying on GNSS for correct functioning. With the
introduction of new GNSSs, like the European Galileo and the Chinese Beidou, in
addition to the existing ones, the United States Global Positioning System (GPS)
and the Russian GLONASS, the applications, accuracy of the position and usage of
the signals are increasing by the day.
Given that GNSS signals are received with very low power, they are prone to
interference events that may reduce the usage or decrease the accuracy. From these
interference, the spoofing attack is the one that has drawn major concerns in the
GNSS community. A spoofing attack consist on the transmission of GNSS-like
signals, with the goal of taking control of the receiver and make it compute an
erroneous position and time solution.
In the thesis, we focus on the design and validation of different signal processing
techniques, that aim at detection and mitigation of the spoofing attack effects. These
are standalone techniques, working at the receiver’s level and providing discrimination
of spoofing events without the need of external hardware or communication
links. Four different techniques are explored, each of them with its unique sets of
advantages and disadvantages, and a unique approach to spoofing detection. For
these techniques, a spoofing detection algorithm is designed and implemented, and
its capabilities are validated by means of a set of datasets containing spoofing signals.
The thesis focuses on two different aspects of the techniques, divided as per detection
and mitigation capabilities. Both detection techniques are complementary, their joint
use is explored and experimental results are shown that demonstrate the advantages.
In addition, each mitigation technique is analyzed separately as they require
specialized receiver architecture in order to achieve spoofing detection and mitigation.
These techniques are able to decrease the effects of the spoofing attacks, to the point
of removing the spoofing signal from the receiver and compute navigation solutions
that are not controlled by the spoofer and lead in more accurate end results.
The main contributions of this thesis are: the description of a multidimensional
ratio metric test for distinction between spoofing and multipath effects; the introduction
of a cross-check between automatic gain control measurements and the
carrier to noise density ratio, for distinction between spoofing attacks and other
interference events; the description of a novel signal processing method for detection
and mitigation of spoofing effects, based on the use of linear regression algorithms;
and the description of a spoofing detection algorithm based on a feedback tracking
architecture
GNSS Integrity Monitoring assisted by Signal Processing techniques in Harsh Environments
The Global Navigation Satellite Systems (GNSS) applications are growing and more pervasive in the modern society. The presence of multi-constellation GNSS receivers able to use signals coming from different systems like the american Global Positioning System (GPS), the european Galileo, the Chinese Beidou and the russian GLONASS, permits to have more accuracy in position solution. All the receivers provide always more reliable solution but it is important to monitor the possible presence of problems in the position computation. These problems could be caused by the presence of impairments given by unintentional sources like multipath generated by the environment or intentional sources like spoofing attacks.
In this thesis we focus on design algorithms at signal processing level used to assist Integrity operations in terms of Fault Detection and Exclusion (FDE). These are standalone algorithms all implemented in a software receiver without using external information. The first step was the creation of a detector for correlation distortion due to the multipath with his limitations. Once the detection is performed a quality index for the signal is computed and a decision about the exclusion of a specific Satellite Vehicle (SV) is taken. The exclusion could be not feasible so an alternative approach could be the inflation of the variance of the error models used in the position computation. The quality signal can be even used for spoofinng applications and a novel mitigation technique is developed and presented. In addition, the mitigation of the multipath can be reached at pseudoranges level by using new method to compute the position solution.
The main contributions of this thesis are: the development of a multipath, or more in general, impairments detector at signal processing level; the creation of an index to measure the quality of a signal based on the detector’s output; the description of a novel signal processing method for detection and mitigation of spoofing effects, based on the use of linear regression algorithms; An alternative method to compute the Position Velocity and Time (PVT) solution by using different well known algorithms in order to mitigate the effects of the multipath on the position domain
Multi-test Detection and Protection Algorithm Against Spoofing Attacks on GNSS Receivers
The vulnerability against interference, spoofing, and jamming of GNSS receivers is considered nowadays a major security concern. This security threat is exacerbated with the existing market availability of GPS jamming and spoofing equipment sold at reasonable prices. If jamming is the main issue faced at present, spoofing, which allows hijacking someone from the expected path, may lead to even worse consequences. Even with the latest security measures that are going to be deployed on the Galileo PRS signals, GNSS receivers are prone to attacks that are relatively easy to implement. In this paper, we identify different countermeasures and security schemes that can be used against spoofing attacks. These countermeasures include some modifications on the GNSS receiver's side, rather than requiring modifications of the whole existing GNSS infrastructure. More specifically, we propose a detection and protection scheme consisting of several statistical tests, based on the computations of moving variances of Doppler offset and C/No estimates, together with a consistency test of the PVT computation. We evaluate the performance of the proposed scheme through simulations and using a measurement setup consisting of a Spirent GSS8000 full constellation simulator whose output is combined with the one from a rooftop GPS antenna before being fed to a receiver front-end. Finally, we compute the probability of detection and false alarm in spoofing detection using the proposed scheme
GNSS interference management techniques against malicious attacks
This thesis collects the outcomes of a Ph.D. course in Telecommunications Engineering and it is focused on the study and design of possible techniques able to counteract interference signal in Global Navigation Satellite System (GNSS) systems. The subject is the jamming threat in navigation systems, that has become a very increasingly important topic in recent years, due to the wide diffusion of GNSS-based civil applications. Detection and mitigation techniques are developed in order to fight out jamming signals, tested in different scenarios and including sophisticated signals. The thesis is organized in two main parts, which deal with management of GNSS intentional counterfeit signals. The first part deals with the interference management, focusing on the intentional interfering signal. In particular, a technique for the detection and localization of the interfering signal level in the GNSS
bands in frequency domain has been proposed. In addition, an effective mitigation technique which exploits the periodic characteristics of the common jamming signals reducing interfering effects at the receiver side has been introduced. Moreover, this technique has been
also tested in a different and more complicated scenario resulting still effective in mitigation and cancellation of the interfering signal, without high complexity. The second part still deals with the problem of interference management, but regarding with more sophisticated signal. The attention is focused on the detection of spoofing signal, which is the most complex among the jamming signal types. Due to this highly difficulty in detect and mitigate this kind of signal, spoofing threat is considered the most dangerous. In this work, a possible techniques able to detect this sophisticated signal has been proposed, observing and exploiting jointly the outputs of several operational block measurements of the
GNSS receiver operating chain
SaPPART White paper. Better use of Global Navigation Satellite Systems for safer and greener transport
Transport and mobility services are crucial to the society that faces important challenges.
Up to date, transport facilities and services have been fundamental to economic growth.
However, there have significant and unacceptable negative impacts on the environment
including pollution, noise and climate change. Therefore, it is paramount that the
efficiency of the transport system is improved significantly including lower consumption
of energy. A way of achieving this is through the concept of smart transport that exploits
Intelligent Transport Systems (ITS) technology. ITS are built on three technology pillars:
information, communication and positioning technologies.
Of the three technologies, positioning could be argued to be the least familiar amongst
transport stakeholders. However, a quick investigation reveals that there are a
wide variety of transport and related services often associated with communication
technologies that are supported by positioning. Currently, the positioning is provided in
the majority of the cases by Global Navigation Satellite System (GNSS), among which
the Global Positioning System (GPS) is the pioneer and still the most widely used
system. The other current fully operational stand-alone system is Russia’s GLONASS.
As these operational systems were not originally and specifically designed for transport
applications, the actual capabilities and limitations of the current GNSS are not fully
understood by many stakeholders. Therefore, better knowledge of these limitations and
their resolution should enable a much more rapid deployment of ITS.
This white paper is produced by the members of the COST Action SaPPART with two
principal aims. The first is to explain the principles, state-of-the-art performance of
GNSS technology and added value in the field of transport. The second aim is to deliver
key messages to the stakeholders to facilitate the deployment of GNSS technology and
thus contribute to the development of smarter and greener transport systems.
The first chapter highlights the important role of positioning in today transport systems
and the added value of accurate and reliable positioning for critical systems.
The second chapter is about positioning technologies for transport: GNSS and their
different aiding and augmentation methods are described, but the other complementary
technologies are also introduced.
The third and last chapter is about the management of performances inside a
positioning-based intelligent transport system, between the positioning system itself
and the application-specific part of the system which processes the raw position for
delivering its service
Machine Learning for Intrusion Detection into Unmanned Aerial System 6G Networks
Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user\u27s needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of the CPS and IoT technologies provided many connected devices, generating an enormous amount of data. Consequently, the innovation of 6G technology is an urgent issue in the coming years. The 6G network architecture is an integration of the satellite network, aerial networks, terrestrial networks, and marine networks. These integrated network layers will provide new enabling technologies, for example, air interfaces and transmission technology. Therefore, integrating heterogeneous network layers guarantees an expansion strategy in the capacity that leads to low latency, ultra-high throughput, and high data rates. In the 6G network, Unmanned Aerial Vehicles (UAVs) are expected to densely occupy aerial spaces as UAV flying base stations (UAV-FBS) that comprise the aerial network layer to offer ubiquitous connectivity and enhance the terrestrial network in remote areas where it is challenging to deploy traditional infrastructure, for example, mountain, ocean deserts, and forest. Although the aerial network layer offers benefits to facilitate governmental and commercial missions, adversaries exploit network vulnerabilities to block intercommunication among nodes by jamming attacks and violating integrity through executing spoofing attacks. This work offers a practical IDS onboard UAV intrusion detection system to detect unintentional interference, intentional interference jamming, and spoofing attacks. Integrating time series data with machine learning models is the main part of the suggested IDF to detect anomalies accurately. This integration will improve the accuracy and effectiveness of the model. The 6G network is expected to handle a high volume of data where non-malicious interference and congestion in the channel are similar to a jamming attack. Therefore, an efficient anomaly detection technique must distinguish behaviors in the drone\u27s wireless network as normal or abnormal behavior. Our suggested model comprises two layers. The first layer has the algorithm to detect the anomaly during transmission. Then it will send the initial decision to the second layer in the model, including two separated algorithms, confirming the initial decision separately (nonintentional interference such as congestion in the channel, intentional interference jamming attack, and classify the type of jamming attack, and the second algorithm confirms spoofing attack. A jamming attack is a stealthy attack that aims to exhaust battery level or block communication to make wireless UAV networks unavailable. Therefore, the UAV forcibly relies on GPS signals. In this case, the adversary triggers a spoofing attack by manipulating the Global Navigation Satellite System (GNSS) signal and sending a fake signal to make UAVs estimate incorrect positions and deviate from their planning path to malicious zones. Hackers can start their malicious action either from malicious UAV nodes or the terrestrial malicious node; therefore, this work will enhance security and pave the way to start thinking about leveraging the benefit of the 6G network to design robust detection techniques for detecting multiple attacks that happen separately or simultaneously
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