Drone Security: Issues and Challenges

Majeed, Rizwan; Abdullah, Nurul Azma; Mushtaq, Muhammad Faheem; Kazmi, Rafaqut

doi:10.14569/ijacsa.2021.0120584

Cited by 14 publications

(9 citation statements)

References 45 publications

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“…Drowns with embedded machine-learning capabilities enable the prediction of jamming attacks by applying Q-learning [10,11] and DQN [12]. Attacks such as intrusion, DDOS, and traffic blockage are managed by a variety of algorithms [13][14][15]; while other research focuses on threats to private and agencies [16,17].…”

Section: Attack Detection and Mitigation Systems For Smart Citiesmentioning

confidence: 99%

Cybersecurity Threats and Mitigations Related to Smart Cities Operation

Domb,

Shnaps

2024

Smart Cities - Foundations and Perspectives [Working Title]

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Smart cities are managed and controlled through comprehensive and complex information systems. The main characteristics of smart cities are expressed in the massive reliance on computerized systems, which comprise large, distributed databases, integrated complex software systems, WAN with a vast number of terminals connected to the Internet and cloud computing, and physical systems fully computerized and remotely controlled. Smart cities are more likely to be sophisticated and more affluent than common cities, making them attractive to cybersecurity attackers motivated by theft and benefits stealing, such as ransom. The concept of smart cities is catching attention across the globe, and it is important in per context of emerging economies. It is inevitable to assume that smart cities incorporate all kinds of system vulnerabilities, which are more likely to be known and exploited by malicious cybersecurity attackers. This chapter elaborates on the leading cybersecurity risks more likely to be encountered in smart cities. We present current concepts and technologies available for mitigating them and provide a comprehensive solution for safe, smart cities.

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Section: Attack Detection and Mitigation Systems For Smart Citiesmentioning

confidence: 99%

Cybersecurity Threats and Mitigations Related to Smart Cities Operation

Domb,

Shnaps

2024

Smart Cities - Foundations and Perspectives [Working Title]

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“…Their overview, however, lacks sensor-based vulnerabilities and attacks. In [73], the authors categorized cyber-security threats into four categories: protocol, sensor, compromised component, and jammers. Their work, however, does not describe individual attacks and countermeasures against them.…”

Section: Related Workmentioning

confidence: 99%

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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“…Drones, while used for the betterment of society, can also be used by the intruders to undertake cyber and physical threats in the network. As the number of drones increase in the network, it becomes very difficult and challenging to identify the harmful drones that may further cause severe threats to the network [14][15][16][17].…”

Section: Motivationmentioning

confidence: 99%

A trust‐based mechanism for drones in smart cities

2022

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Smart cities equipped with intelligent devices can enhance the lifestyle and quality of humans by automatically and collaboratively acting as a sustainable resource to the ecosystem. In addition, the technological advancement can be further empowered by interconnecting various types of technologies, such as IoT, Artificial Intelligence, drones and robotics which will clearly improve the Quality of Services, energy efficiency and connectivity to the overall system. The integration of drones hovering over smart cities with the other devices in the smart city network brings a lot of benefits. However, it can also lead to various security and privacy concerns in the network. The aim of this article is to put forward a secure and safe smart city communication environment by proposing a trust establishment scheme for the ad hoc Unmanned Aerial Vehicles network. In which, malicious devices can be traced and blocked by analysing and evaluating their historical interactions within the system and calculating their trust values. A behaviour‐based and local trust value scheme is used to analyse the trust of each communicating device that is further associated with a blockchain distributed ledger. The proposed mechanism is measured over various networking and security metrics, including throughput, latency, accuracy and block updating compared to the existing state‐of‐the‐art solutions.

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Drone Security: Issues and Challenges

Cited by 14 publications

References 45 publications

Cybersecurity Threats and Mitigations Related to Smart Cities Operation

Cybersecurity Threats and Mitigations Related to Smart Cities Operation

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

A trust‐based mechanism for drones in smart cities

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