Unmanned Aerial Vehicle Security Using Recursive Parameter Estimation

Birnbaum, Zachary; Dolgikh, Andrey; Skormin, Victor A.; O’Brien, Edward E.; Müller, Daniel; Stracquodaine, Christina

doi:10.1007/s10846-015-0284-1

Cited by 43 publications

(18 citation statements)

References 10 publications

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“…The security targets the location of the particular network node in the architecture. Birnbaum et al have also worked on the security aspects of the UAVs. The work primarily focuses on the identification of network attacks and hardware failures that might hinder the network operations.…”

Section: Related Workmentioning

confidence: 99%

Teredo tunneling‐based secure transmission between UAVs and ground ad hoc networks

Sharma

Kumar

2016

Int J Communication

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SUMMARYCoordination between distributed ad hoc units requires ambient intelligence to form a guidance system. The network formed by this coordination comprises two variedly operating ad hoc units. One such coordinating network is formed between the unmanned aerial vehicles (UAVs) and the ground nodes. Such network formations require highly sensitive and fault-tolerant data transfer over the secure channels. A secure channel is required that can ensure the secure connectivity between nodes of the two networks. This secure channel can be realized using a teredo tunneling approach. Using this approach, a service-oriented security framework is developed. The proposed framework focuses over security in terms of cognitive, corridor, and localization of the multi-UAV guided system based on the estimation of teredo units using Gauss-Markov-based˛ ˇ filter. The effectiveness of the proposed approach is demonstrated, with significant improvements in terms of system fairness, data delivery ratio, network throughput, and average delays in comparison with the baseline and Hubenko architecture. The proposed model provides 16.25% better fairness, 12% better data rate, 15.7% better throughput, and 10.3% lesser delays than the baseline and 12.9% better fairness, 10% better data rate, 8% better throughput, and 7.9% lesser delays than the Hubenko architecture.

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Section: Related Workmentioning

confidence: 99%

Teredo tunneling‐based secure transmission between UAVs and ground ad hoc networks

Sharma

Kumar

2016

Int J Communication

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“…While effective to a certain extent, these methods suffer from the limitations of low performance and high cost. Therefore, in order to reliably manage UAVs, it is recommended that every UAV should have an effective control and management system [1]. The system is required to alert registered UAV users or operators when they are about to enter a no-fly zone or when to avoid certain areas, such as where emergency responders are active.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, it is paramount to firstly, specify the RNP and then the corresponding positioning and navigation system. In this process, the level of criticality of each mission or application must be considered, usually categorized into: (1) high, for missions related to safety-of-life and military activities; (2) medium, for commercial/liability critical missions (e.g., UAVs for delivery applications); and (3) low, for non-mission critical applications (e.g., private UAVs for domestic use). Hence, to cater for different levels of criticality, navigation systems must meet the targets for the RNP parameters of accuracy, integrity, continuity, and availability [4].…”

Section: Introductionmentioning

confidence: 99%

“…Once the HPE exceeds the HAL, the maximum allowable value, the system exhibits loss of integrity. Given that the empirical distribution usually tends to have much heavier tails than Gaussian, we specify the value of HAL as 50 m. The specification of HAL seems to be generous on account that: (1) we are more pessimistic in the "tails" of error distribution; (2) the overbounding value, i.e., HPL, should be between HPE and HAL, thus the HAL should not be too tight to ensure the basic availability of the system.…”

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confidence: 99%

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GNSS/INS Integration with Integrity Monitoring for UAV No-fly Zone Management

et al. 2020

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The rapidly increasing use of unmanned aerial vehicles pose a significant challenge to no-fly zone management. The vehicle state in flight should be available for the whole mission, enabling an alert to be issued to the relevant users and entities at an appropriate time and location before intrusion into a no-fly zone. In addition to spatial databases and other control mechanisms, the navigation system used must have the required accuracy, integrity, continuity, and availability. In this paper, the accuracy and integrity requirements, and the positioning system for no-fly zone unmanned aerial vehicle management are specified. The proposed positioning system integrates global navigation satellite systems (GNSS) and inertial navigation system (INS) in the measurement domain. An integrity monitoring layer is incorporated for fault detection and exclusion as well as real-time horizontal protection level computation functions. Experimental results show that the algorithm proposed is capable of delivering accuracy and integrity requirements for unmanned aerial vehicle (UAV) no-fly zone management.

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“…The method by Han et al [3] uses RLS for quadrotor actuator fault detection and devises a parity space approach to estimate the forgetting factor for RLS. The method proposed by Birnbaum et al [14] applies RLS to the given model for UAV and performs estimation and tracking of the controller parameters. It processes the data in batches of size 500 samples and compares the parameters of different batches to detect discrepancies indicating anomalies.…”

Section: Introductionmentioning

confidence: 99%

Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles

Keipour

Mousaei

Scherer

2019

2019 International Conference on Robotics and Automation (ICRA)

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The recent increase in the use of aerial vehicles raises concerns about the safety and reliability of autonomous operations. There is a growing need for methods to monitor the status of these aircraft and report any faults and anomalies to the safety pilot or to the autopilot to deal with the emergency situation. In this paper, we present a real-time approach using the Recursive Least Squares method to detect anomalies in the behavior of an aircraft. The method models the relationship between correlated input-output pairs online and uses the model to detect the anomalies. The result is an easy-to-deploy anomaly detection method that does not assume a specific aircraft model and can detect many types of faults and anomalies in a wide range of autonomous aircraft. The experiments on this method show a precision of 88.23%, recall of 88.23% and 86.36% accuracy for over 22 flight tests. The other contribution is providing a new fault detection open dataset for autonomous aircraft, which contains complete data and the ground truth for 22 fixed-wing flights with eight different types of mid-flight actuator failures to help future fault detection research for aircraft.

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Unmanned Aerial Vehicle Security Using Recursive Parameter Estimation

Cited by 43 publications

References 10 publications

Teredo tunneling‐based secure transmission between UAVs and ground ad hoc networks

Teredo tunneling‐based secure transmission between UAVs and ground ad hoc networks

GNSS/INS Integration with Integrity Monitoring for UAV No-fly Zone Management

Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles

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