Spatial GNSS Spoofing Against Drone Swarms With Multiple Antennas and Wiener Filter

Ceccato, Marco; Formaggio, F; Tomasin, Stefano

doi:10.1109/tsp.2020.3028752

Cited by 18 publications

(9 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the concept of swarm formation plays a vital role in this case as transmitting a signal relative to any individual drone in the swarm might create obvious changes in the FANET's shape. This observation is considered by Ceccato et al [56] in 2020 to design a spoofing tool against FANET to divert the routes of the entire swarm without disrupting the formation. This is called 'Spatial Spoofing', where FANETs move in the spoofed area in formation as if they are moving in their real target area.…”

Section: A Gps Spoofing Attack Mechanisms In Uavsmentioning

confidence: 99%

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

Altaweel,

Mukkath,

Kamel

2023

IEEE Access

View full text Add to dashboard Cite

Flying Ad-Hoc Networks (FANETs) are groups of UAVs connected in an Ad-Hoc manner to accomplish a common mission. The widespread acceptance of UAVs due to their low cost and high efficiency has attracted malicious security attacks against them. These attacks cannot be easily prevented due to UAVs' limited computational power, short battery life, and inability to execute complex algorithms. FANETs rely on the Global Positioning System (GPS) for localization. GPS Spoofing, an easy-to-launch attack, is one of the main challenges in FANETs. In which, the legitimate and not-encrypted civilian GPS signals are overridden by counterfeit signals to deceive the UAVs to collide or to be hijacked. Researchers proposed various countermeasures to address GPS Spoofing attacks in FANETs. To further assist future research, this paper provides a systematic literature review on GPS Spoofing attacks in FANETs and their defense mechanisms. After formulating eight research questions and applying well-defined inclusion/exclusion criteria and quality assessment tools, 70 research articles were extracted. The existing defense mechanisms were classified based on their objectives (i.e., detection, mitigation, and/or prevention) and according to their basis (i.e., relying on readings from various drones' devices/sensors, processing the signals received by various sensors, employing machine learning algorithms, relying on game theory, or leveraging cryptographic techniques to authenticate and protect the confidentiality of GPS signals). The defense mechanisms were also analyzed to identify the attacker models, impacts of the attack, and detection performance. This study found that most of the proposed methods are detection approaches, rather than mitigation or prevention. Also, almost all papers used simulation experiments rather than a proof-of-concept implementation, which does not demonstrate a convincing performance under realistic mobility and propagation models. Moreover, most solutions addressed GPS Spoofing for a single UAV. Only eight articles addressed multiple UAV scenarios and none of them provided a proof-of-concept evaluation. INDEX TERMSDrones, unmanned ariel vehicle (UAV), Flying Ad-Hoc NETwork (FANET), GPS spoofing attack, wireless network security, systematic literature review. * Spoofing tools such as simulators, repeaters, etc. * Spoofing techniques such as position denial and track break. * Spoofer location such as remote, onboard, and escort. --Defense mechanisms against GPS Spoofing: the research articles that discuss various mechanisms to defend against GPS Spoofing attacks in UAVs. These articles are further classified based on their objectives as follows: * Detection of GPS Spoofing attacks. * Mitigation the damage caused by GPS Spoofing attacks. * Prevention of GPS Spoofing. The defense mechanisms are also classified according to their basis as follows: * The use of devices/sensors on the drones. * Signal processing techniques applied on various signals received by various sensors on the drone. * Cryptographic techn...

show abstract

Section: A Gps Spoofing Attack Mechanisms In Uavsmentioning

confidence: 99%

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

Altaweel,

Mukkath,

Kamel

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…From ( 1) and (7), it is clear that both expressions are identical except for notational differences. Therefore, if the number of spoofers and the number of visible satellites are equal, both hypotheses are identical and the detector presented in this work cannot differentiate between them.…”

Section: System Modelmentioning

confidence: 99%

“…However, GNSS technology may be vulnerable to malicious attacks, notably jamming, meaconing, replaying/relaying, and spoofing [3]- [7]: Jamming can prevent navigation signal acquisition and degrade or deny positioning and synchronization altogether. Meaconing/replaying and spoofing can manipulate the position (and the time correction) computed by the victim GNSS receivers.…”

Section: Introductionmentioning

confidence: 99%

Multiple Spoofer Detection for Mobile GNSS Receivers Using Statistical Tests

2021

View full text Add to dashboard Cite

We consider Global Navigation Satellite Systems (GNSS) spoofing attacks and devise a countermeasure appropriate for mobile GNSS receivers. Our approach is to design detectors that, operating after the signal acquisition, enable the victim receiver to determine with high probability whether it is under a spoofing attack or not. Namely, the binary hypothesis is that either the GNSS receiver tracks legitimate satellite signals, H 0 , or spoofed signals, H 1 . We assume that there exists an unknown number of multiple spoofers in the environment and the attack strategy (which legitimate signals are spoofed by which spoofers) is not known to the receiver. Based on these assumptions, we propose an algorithm that identifies the number of spoofers and clusters the spoofing data by using Bayesian information criterion (BIC) rule. Depending on the estimated and clustered data we propose a detector, called as generalized likelihood ratio (GLRT)like detector. We compare the performance of the GLRT-like detector with a genie-aided detector in which the attack strategy and the number of spoofers is known by the receiver. In addition to this, we extend the GLRT-like detector for the case where the noise variance is also unknown and present the performance results.

show abstract

“…To solve the first limitation, we first sort and list the key techniques of GNSS spoofing (i.e. a relatively easily achieved generative spoofing [20], a more complex generative spoofing [7], and forwarding spoofing [21]) and anti‐spoofing (i.e. the anti‐spoofing technologies based on the encryption and authentication of navigation signals [22], the signal characteristics [23], and the auxiliary information [24]) and their features (i.e.…”

Section: Introductionmentioning

confidence: 99%

Optimal decision for the satellite navigation system under navigation countermeasures based on spoofing effect evaluation results

Wang

Sun

Wang

2023

IET Control Theory & Appl

View full text Add to dashboard Cite

This paper realizes the evaluation and optimal decision of the spoofing effect on the global navigation satellite system (GNSS) under navigation countermeasures based on the game perspective, to overcome the limitations of current relevant research findings and maintain the secure application of the GNSS and maximize its defensive benefit during countering. An evaluation system based on the perspective of the game between spoofing strategies and defense measures is created to build the benefit matrix, which can solve the limitation in building a benefit matrix (the vital element in a game) that conforms to the confrontation‐oriented GNSS spoofing properties. Based on the built benefit matrix, a method integrating the grey expert‐based system with the hybrid evolutionary method is developed to realize quantifying the matrix and further make the optimal decision stably, which can solve the uncertainties of qualitative indices during quantifying and no global optimal solution for benefit equations deduced from the quantified matrix. Finally, based on various judgment principles, simulation and testing results verify the effectiveness of the obtained results and the superiority of the proposed method by comparing the results solved by the method in this paper with the results obtained by other decision‐making processing methods.

show abstract

Spatial GNSS Spoofing Against Drone Swarms With Multiple Antennas and Wiener Filter

Cited by 18 publications

References 23 publications

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

Multiple Spoofer Detection for Mobile GNSS Receivers Using Statistical Tests

Optimal decision for the satellite navigation system under navigation countermeasures based on spoofing effect evaluation results

Contact Info

Product

Resources

About