Analyzing two connectivities in UAV-ground mobile ad hoc networks

Xu, Zhezhuang; Huo, Jinhai; Yuan, Jian; Shan, Xiuming; Feng, Zhenming

doi:10.1109/csae.2011.5952445

Cited by 6 publications

(1 citation statement)

References 8 publications

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“…Xu et al [7] is a study that secures the communication connection between manned vehicles and UAVs; it proposes how to secure the communication connections between several manned vehicles and a UAV and several manned vehicles and several UAVs. Though the study in [7] may be similar to the scheme that we suggest, and it focuses on maintaining the connection between vehicles and UAVs while they are moving. However, it does not consider how to address the situation in case UAVs encounter obstacles while they are moving.…”

Section: Related Workmentioning

confidence: 99%

An Obstacle Avoidance Scheme Maintaining Connectivity for Micro-Unmanned Aerial Vehicles

Choi

et al. 2014

International Journal of Distributed Sensor Networks

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This paper suggests an obstacle avoidance scheme that enables a group of micro-UAV (Unmanned Aerial Vehicles) to avoid colliding with an obstacle that is found in the course of the flight. This scheme considers a method for UAVs to avoid colliding with such obstacles and a plan of action for when the UAVs in the group lose connectivity during flight. The main goal is for UAVs to reach the target without colliding with any obstacles. To achieve this goal, directly after the UAVs avoid the obstacle at a raised altitude above it, they fly at a higher altitude for a while and then descend to their original height. When this approach is judged to be inefficient because the height of the obstacle is too high, the UAVs divide into two groups and move to either side of it while continuing to fly at the same altitude, thereby avoiding the obstacle. Afterwards, they gather into one group again. We verify the proposed scheme and do the performance evaluation by ns-2.

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Section: Related Workmentioning

confidence: 99%

An Obstacle Avoidance Scheme Maintaining Connectivity for Micro-Unmanned Aerial Vehicles

Choi

et al. 2014

International Journal of Distributed Sensor Networks

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Analysis of Routing Attacks in FANETs

Ozlem

Pinar

Şen

2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Unmanned aerial vehicles (UAVs) in flying ad-hoc networks (FANETs) face security challenges due to the dynamic and distributed nature of these networks. This paper presents the Federated Learning-based Intrusion Detection System (FL-IDS), an innovative approach designed to improve FANET security. FL-IDS leverages federated learning to address privacy concerns of centralized intrusion detection systems. FL-IDS operates in a decentralized manner, enabling UAVs to collaboratively train a global intrusion detection model without sharing raw data. Local models are assigned to each UAV, using client-specific data, and only updated model weights are shared with a central server. This preserves privacy while utilizing collective intelligence for effective intrusion detection. Experimental results show FL-IDS's competitive performance with Central IDS (C-IDS) while mitigating privacy concerns. The Bias Towards Specific Clients (BTSC) method further enhances FL-IDS performance, surpassing C-IDS even at lower attacker ratios. A comparative analysis with traditional intrusion detection methods, including Local IDS (L-IDS), provides insights into FL-IDS's strengths. This study significantly contributes to FANET security by introducing a privacy-aware, decentralized intrusion detection approach tailored to the unique challenges of UAV networks.

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