Frequency-based detection of replay attacks: application to a quadrotor UAV

Sánchez, Helem Sabina; Rotondo, Damiano; Vidal, Marc López; Quevedo, Joseba

doi:10.1109/icsc47195.2019.8950619

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…In summary, physical layer security in UAVs involves employing a combination of different techniques to protect the wireless communication link from unauthorized access, interference, and interception and allows to ensure reliable and secure wireless communication between the UAVs and the GCS. [103] Detection mechanisms and introduction of a timestamp [126,131,132] Unencrypted radio communication Eavesdropping attack [133] Encrypted and authenticated communication [52],…”

Section: Physical Layer Securitymentioning

confidence: 99%

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A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

Mykytyn,

Brzozowski,

Dyka

et al. 2024

CMES

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The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this survey is to extensively review state-of-the-art literature regarding common sensor-and communication-based vulnerabilities, existing threats, and active or passive cyberattacks against UAVs, as well as shed light on the research gaps in the literature. In this work, we describe the Unmanned Aerial System (UAS) architecture to point out the origination sources for security and safety issues. We evaluate the coverage and completeness of each related research work in a comprehensive comparison table as well as classify the threats, vulnerabilities and cyber-attacks into sensor-based and communication-based categories. Additionally, for each individual cyber-attack, we describe existing countermeasures or detection mechanisms and provide a list of requirements to ensure UAV's security and safety. We also address the problem of implausible sensor measurements and introduce the idea of a plausibility check for sensor data. By doing so, we discover additional measures to improve security and safety and report on a research niche that is not well represented in the current research literature. KEYWORDSUnmanned aerial vehicle; unmanned aerial system; cyber security and privacy; drone swarm; security vulnerabilities; cyber-threats; cyber-attacks; plausibility check Nomenclature UAV Unmanned aerial vehicle UAS Unmanned aerial system GCS Ground control station IMU Inertial measurement unit FDI Fault detection and isolation FTC Fault tolerant control 1020

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Section: Physical Layer Securitymentioning

confidence: 99%

“…In [131], the authors simulated a frequency based Replay attack detection mechanism by comparing the energy of a sine wave with a time-varying frequency introduced into the closed-loop system. They checked if the time profile of the frequency components in the output signal is compatible with the authentication signal.…”

Section: Physical Layer Securitymentioning

confidence: 99%

A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

Mykytyn,

Brzozowski,

Dyka

et al. 2024

CMES

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“…In addition, we can also consider the potential consequences of a successful replay attack by mathematical formulation: Let C denote the potential cost or harm caused by a successful attack. Then, a model of the expected cost of a replay attack can be written as E(C) = P(success) * C. This formulation helps us to quantify the potential impact of a replay attack and can guide our efforts to implement effective security measures to prevent such attacks [35].…”

mentioning

confidence: 99%

A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

Airlangga

Liu

2023

Drones

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An unmanned aerial vehicle (UAV) is an autonomous flying robot that has attracted the interest of several communities because of its capacity to increase the safety and productivity of labor. In terms of software engineering, UAV system development is extremely difficult because the focus is not only on functional requirement fulfillment, but also on nonfunctional requirements such as security and safety, which play a crucial role in mission success. Consequently, architecture robustness is very important, and one of the most common architectures developed is based on a centralized pattern in which all UAVs are controlled from a central location. Even though this is a very important problem, many developers must expend a great deal of effort to adapt and improve security. This is because there are few practical perspectives of security development in the context of UAV system development; therefore, the study of attack and defense patterns in centralized architecture is required to fill this knowledge gap. This paper concentrates on enhancing the security aspect of UAV system development by examining attack and defense patterns in centralized architectures. We contribute to the field by identifying 26 attack variations, presenting corresponding countermeasures from a software analyst’s standpoint, and supplying a node.js code template for developers to strengthen their systems’ security. Our comprehensive analysis evaluates the proposed defense strategies in terms of time and space complexity, ensuring their effectiveness. By providing a focused and in-depth perspective on security patterns, our research offers crucial guidance for communities and developers working on UAV-based systems, facilitating the development of more secure and robust solutions.

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A Machine Learning Based Approach to Detect Cyber-Attacks on Connected and Autonomous Vehicles (CAVs)

Nazaruddin,

Chaudhry

2023

Advanced Sciences and Technologies for Security Applications

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Frequency-based detection of replay attacks: application to a quadrotor UAV

Cited by 7 publications

References 21 publications

A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

A Machine Learning Based Approach to Detect Cyber-Attacks on Connected and Autonomous Vehicles (CAVs)

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