UAV Sensor Spoofing Detection Algorithm Based on GPS and Optical Flow Fusion

Meng, Lianxiao; Ren, Shuangyin; Tang, Gaigai; Yang, Chao; Wu, Yang

doi:10.1145/3377644.3377670

Cited by 17 publications

(4 citation statements)

References 10 publications

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“…Such control invariants are derived from physical dynamics and control systems [127] . For instance, the data of GPS and optical flow sensors can be used to validate against other sensor data to detect inconsistencies to detect such attacks [133] .…”

Section: Uav Neutralizing Techniquesmentioning

confidence: 99%

A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques

et al. 2021

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Unmanned Aerial Vehicles (UAV) have revolution- ized the aircraft industry in this decade. UAVs are now capable of carrying out remote sensing, remote monitoring, courier delivery, and a lot more. A lot of research is happening on making UAVs more robust using energy harvesting techniques to have a better battery lifetime, network performance and to secure against attackers. UAV networks are many times used for unmanned missions. There have been many attacks on civilian, military, and industrial targets that were carried out using remotely controlled or automated UAVs. This continued misuse has led to research in preventing unauthorized UAVs from causing damage to life and property. In this paper, we present a literature review of UAVs, UAV attacks, and their prevention using anti-UAV techniques. We first discuss the different types of UAVs, the regulatory laws for UAV activities, their use cases, recreational, and military UAV incidents. After understanding their operation, various techniques for monitoring and preventing UAV attacks are described along with case studies.

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Section: Uav Neutralizing Techniquesmentioning

confidence: 99%

A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques

et al. 2021

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“…Secondly, EV manufacturers may remove the possibility of integrating fake sensors, which auto repairers sometimes do in the market with the aim of data spoofing into embedded circuits associated with EVs or charging stations or to spoof sensory data. Implementing the cross-controller authentication of sensors and EV circuits [154] would protect against spoofing. In addition, there should be a majority sensor voting mechanism in case there exist redundant sensors to ensure data integrity [155].…”

Section: Sensor-based Attacksmentioning

confidence: 99%

Emerging Cybersecurity and Privacy Threats to Electric Vehicles and Their Impact on Human and Environmental Sustainability

et al. 2023

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With the global energy crisis, increasing demand, and a national-level emphasis on electric vehicles (EVs), numerous innovations are being witnessed throughout the EV industry. EVs are equipped with sensors that maintain a sustainable environment for the betterment of society and enhance human sustainability. However, at the same time, as is the case for any new digital technology, they are susceptible to threats to security and privacy. Recent incidents demonstrate that these sensors have been misused for car and energy theft, financial fraud, data compromise, and have caused severe health and safety problems, amongst other things. To the best of our knowledge, this paper provides a first systematic analysis of EV sustainability, digital technologies that enhance sustainability, their potential cybersecurity threats, and corresponding defense. Firstly, three robust taxonomies have been presented to identify the dangers that can affect long-term sustainability domains, including (1) life and well-being, (2) safe environment, and (3) innovation and development. Second, this research measures the impact of cybersecurity threats on EVs and correspondingly to their sustainability goals. Third, it details the extent to which specific security controls can mitigate these threats, thereby allowing for a smooth transition toward secure and sustainable future smart cities.

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“…Lianxiao et al [74] proposed an approach that applied the fusion of the GPS and optical flow sensors to detect GPS Spoofing attacks in UAVs. The distance obtained by GPS coordinates of two positions traversed by a UAV and the pixel distance of images collected by optical flow sensors at these locations is compared.…”

Section: B Gps Spoofing Defense Mechanisms In Uavsmentioning

confidence: 99%

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

Altaweel,

Mukkath,

Kamel

2023

IEEE Access

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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...

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UAV Sensor Spoofing Detection Algorithm Based on GPS and Optical Flow Fusion

Cited by 17 publications

References 10 publications

A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques

A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques

Emerging Cybersecurity and Privacy Threats to Electric Vehicles and Their Impact on Human and Environmental Sustainability

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

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