Adaptive Air-to-Ground Secure Communication System Based on ADS-B and Wide-Area Multilateration

Nijsure, Yogesh; Kaddoum, Georges; Gagnon, Ghyslain; Gagnon, François; Yuen, Chau; Mahapatra, Rabi

doi:10.1109/tvt.2015.2438171

Cited by 51 publications

(20 citation statements)

References 25 publications

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“…In order to resolve these security issues, the authors of [182] proposed a secure geographical routing protocol by exploiting the benefits of the greedy perimeter stateless routing of [183] and of the ADS-B protocol. Nijsure et al [184] developed Angle-Of-Arrival (AOA), Time-Difference-Of-Arrival (TDOA) and Frequency-Difference-Of-Arrival (FDOA) techniques in order to provide additional safeguards against ADS-B security threats and for aircraft discrimination. Furthermore, Nijsure et al also implemented a software-defined-radio-based hardware prototype for facilitating AOA/TDOA/FDOA.…”

Section: Security Mechanismsmentioning

confidence: 99%

Aeronautical $Ad~Hoc$ Networking for the Internet-Above-the-Clouds

Chen²,

et al. 2019

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The engineering vision of relying on the "smart sky" for supporting air traffic and the "Internet above the clouds" for in-flight entertainment has become imperative for the future aircraft industry. Aeronautical ad hoc Networking (AANET) constitutes a compelling concept for providing broadband communications above clouds by extending the coverage of Air-to-Ground (A2G) networks to oceanic and remote airspace via autonomous and self-configured wireless networking amongst commercial passenger airplanes. The AANET concept may be viewed as a new member of the family of Mobile ad hoc Networks (MANETs) in action above the clouds. However, AANETs have more dynamic topologies, larger and more variable geographical network size, stricter security requirements and more hostile transmission conditions. These specific characteristics lead to more grave challenges in aircraft mobility modeling, aeronautical channel modeling and interference mitigation as well as in network scheduling and routing. This paper provides an overview of AANET solutions by characterizing the associated scenarios, requirements and challenges. Explicitly, the research addressing the key techniques of AANETs, such as their mobility models, network scheduling and routing, security and interference are reviewed. Furthermore, we also identify the remaining challenges associated with developing AANETs and present their prospective solutions as well as open issues. The design framework of AANETs and the key technical issues are investigated along with some recent research results. Furthermore, a range of performance metrics optimized in designing AANETs and a number of representative multi-objective optimization algorithms are outlined.

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Section: Security Mechanismsmentioning

confidence: 99%

Aeronautical $Ad~Hoc$ Networking for the Internet-Above-the-Clouds

Chen²,

et al. 2019

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“…The complementary problem of optimal sensor selection during the online aircraft tracking phase is addressed in [2]. This presupposes that (a) the existing sensor network infrastructure was thoughtfully deployed and (b) if the sensors are properly chosen, an acceptable end-to-end GDOP value can be attained.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, an over-densification of receivers in the same area does not necessarily improve the deployment gain in terms of coverage and does not facilitate the application of data fusion or multilateration-based mechanisms. Wide-area multilateration (WAM) based on Time Difference Of Arrival (TDOA) measurements is one of the preferred methods for verifying the accuracy and integrity of ADS-B position reports [1,2]. This is, however, only possible if the target aircraft is visible from at least four ground-based receivers.…”

Section: Introductionmentioning

confidence: 99%

On ADS-B Sensor Placement for Secure Wide-Area Multilateration

Darabseh

Bitsikas

Tedongmo

et al. 2020

8th OpenSky Symposium 2020

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As automatic dependent surveillance–broadcast (ADS-B) becomes more prevalent, the placement of on-ground sensors is vital for Air Traffic Control (ATC) to control the airspace. However, the current sensors are placed in an unstructured way that keeps some areas without coverage, and others are over-densified by sensors. Therefore, areas with coverage anomalies may cause issues that inhibit accurate ADS-B verifications as well as the availability of ADS-B altogether. In this paper, we tackle the ADS-B-specific optimal sensor placement (OSP) problem. Of importance are both the optimal coverage and the secure and accurate verification of received ADS-B messages. Specifically, we take into account the following objectives. First, we determine the minimum required number of sensors in order to cover a certain area like Europe. Second, we produce a better placement of the current sensors with respect to the security and accuracy of geometric dilution of precision (GDOP). Finally, we calculate how far the current sensor setup is from our derived optimal solution as well as the cost to reach the optimality. Our experiments show that the ideal fitness score for solving the OSP is below 0.1, meaning that the mean squared error (MSE) of the required and achieved GDOPs is significantly small, thus accomplishing a near-optimal setup.

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“…These facts make the usage of synchronous and asynchronous TDOA deployments dependent on the environment characteristics. In this paper, we will analyze the asynchronous TDOA architecture since it supposes a promising technology in LPS that requires the solution of the Node Location Problem (NLP) to any application scenario and due to the extent usage of TDOA positioning in terrestrial localization [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Memetic Algorithm for the Node Location Problem in Local Positioning Systems

Díez-González

Verde

Ferrero-Guillén

et al. 2020

Sensors

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Local Positioning Systems (LPS) have shown excellent performance for applications that demand high accuracy. They rely on ad-hoc node deployments which fit the environment characteristics in order to reduce the system uncertainties. The obtainment of competitive results through these systems requires the solution of the Node Location Problem (finding the optimal cartesian coordinates of the architecture sensors). This problem has been assigned as NP-Hard, therefore a heuristic solution is recommended for addressing this complex problem. Genetic Algorithms (GA) have shown an excellent trade-off between diversification and intensification in the literature. However, in Non-Line-of-Sight (NLOS) environments in which there is not continuity in the fitness function evaluation of a particular node distribution among contiguous solutions, challenges arise for the GA during the exploration of new potential regions of the space of solutions. Consequently, in this paper, we first propose a Hybrid GA with a combination of the GA operators in the evolutionary process for the Node Location Problem. Later, we introduce a Memetic Algorithm (MA) with a Local Search (LS) strategy for exploring the most different individuals of the population in search of improving the previous results. Finally, we combine the Hybrid Genetic Algorithm (HGA) and Memetic Algorithm (MA), designing an enhanced novel methodology for solving the Node Location Problem, a Hybrid Memetic Algorithm (HMA). Results show that the HMA proposed in this article outperforms all of the individual configurations presented and attains an improvement of 14.2% in accuracy for the Node Location Problem solution in the scenario of simulations with regards to the previous GA optimizations of the literature.

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Adaptive Air-to-Ground Secure Communication System Based on ADS-B and Wide-Area Multilateration

Cited by 51 publications

References 25 publications

Aeronautical $Ad~Hoc$ Networking for the Internet-Above-the-Clouds

Aeronautical $Ad~Hoc$ Networking for the Internet-Above-the-Clouds

On ADS-B Sensor Placement for Secure Wide-Area Multilateration

Hybrid Memetic Algorithm for the Node Location Problem in Local Positioning Systems

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