A Key Management Module for Secure ADS-B

Technological independence is important for every country in global competition. One of the technological advancements developed by the Indonesian government through BPPT is Automatic Dependent Surveillance Broadcast (ADS-B) type in, which functions as a flight monitoring system. The Indonesian Air Force (TNI AU) through Depohar 50 (Depot Maintenance 50) has also developed ADS-B type in, which is currently deployed in six radar units known as the Flight Monitoring System (FMS) Mode-S. Accordance with government regulations (Minister of Transportation Regulation No. 81 of 2017), the government has mandated the use of ADS-B for flight safety. ADS-B has two types, in and out. In the TNI AU, ADS-B out is installed on aircraft such as Grob, KT-1, and Cessna, while ADS-B in is installed on Weibel radar. However, since ADS-B is not yet installed on TNI AU aircraft, flight data from the Air Traffic Control (ATC) was communicated to the pilots, hence, they can be aware of the air traffic situation. Furthermore, due to the increasing air traffic, communication with ATC has become limited. A qualitative method was used in the development of the ADS-B type in TNI AU aircraft, and the previous ADS-B type in development could only be installed on the ground station. The information received from ADS-B on the aircraft was real-time air traffic, which helps pilots make decisions to enhance flight safety, such as reducing the risk of aircraft collisions. The use of this technology on TNI AU aircraft is important for improving flight safety and technological independence.

Operations in the Next Generation Air Transportation System (NextGen) are planned to have a reduced dependency on primary surveillance radar and use Automatic Dependent Surveillance - Broadcast (ADS-B) to provide aircraft state information to Air Traffic Control (ATC) and onboard collision detection and avoidance systems. With the ongoing integration of Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS), ADS-B is expected to become the main surveillance input to UAS collision avoidance. Traffic Alert and Collision Avoidance System (TCAS) is unable to meet requirements in terms of adaptability to future operations with reduced separation margins, addition of new user groups (e.g., UAS), and support of additional surveillance inputs. Airborne Collision Avoidance System (ACAS X) is being designed to meet these requirements and to increase surveillance, alerting, and resolution performance. The RTCA has released Minimum Operational Performance Standards (MOPS) to provide system and operational performance characteristics that ADS-B must provide. This paper analyzes recorded ADS-B data from test flights that were performed in the Continental U.S. (CONUS) and verifies measured performance with specified operational characteristics in terms of coverage, accuracy, and integrity.

Automatic Dependent Surveillance Broadcast (ADSB) is one of the most prominent surveillance protocols for Air Traffic Control (ATC) that has gained great momentum in recent years. This has been motivated by several advantages it brings to the table, compared to traditional surveillance protocols, such as higher location accuracy, lower deployment and maintenance costs, and better financial viability. This led to the deployment of ADS-B in several parts of the world including Europe, China and USA. However, despite these numerous benefits, there have been reports of serious security flaws that could be exploited by a variety of cyber attacks, which may hinder the wider adoption of this technology. There were several techniques to deal with this important problem including secure location verification, cryptography, and Artificial Intelligence (AI). This latter has an edge over the two others as no modification to the original protocol and no special requirements, such as clock synchronization or number of nodes, are needed. In this context, novel AI-based classifiers for threat detection are constantly emerging and one of the most promising ones is Transformer Neural Networks known as Transformers. In this paper, we propose a novel approach for detecting replay attacks targeting ADS-B using a model based on transformers. We validate our findings with a performance evaluation of our model in comparison with other deep learning classifiers. Our results show that our model outperformed all other classifiers with regards to the performance metrics we used which indicate a promising success of our approach.

In this paper, we develop a novel method to detect Global Navigation Satellite Systems (GNSS) spoofing for an Automatic Dependent Surveillance-Broadcast (ADS-B) equipped aircraft. The Federal Aviation Administration (FAA) has mandated [18] all civil aircraft to be ADS-B Out equipped by January 1, 2020. The ADS-B Out broadcast sent to Air Traffic Control (ATC) consists of the aircraft's position, velocity, and other aircraft-specific information, all of which being unencrypted, poses a serious integrity threat. With readily available ADS-B trackers [19], [20], a spoofer can accurately track an aircraft to generate a spoofed trajectory that can go undetected [11]. We propose a novel method to modulate the ADS-B Out position broadcast such that a spoofed trajectory generated using the modulated ADS-B will be detectable by comparing Inertial Navigation System (INS) positions against those obtained using the spoofed GNSS signal. The amplitude of ADS-B modulation is selected to exceed the nominal INS error covariance so that spoofing is observable. In this work, we analytically quantify the magnitude of ADS-B modulation that will be sufficient for spoofing detection. During scenarios of GNSS signal jamming and spoofing, reauthentication of a reacquired GNSS signal is necessary to maintain integrity. During a GNSS outage, given enough time, the INS solution drift will grow large enough such that the spoofed GNSS solution might be within the INS error covariance envelope and go undetected. For GNSS outage scenarios we propose continuous modulation of ADS-B position and analytically quantify the magnitude such that spoofing of the GNSS signal is detectable after signal is re-acquired.

ADS-B (Automatic Dependent Surveillance – Broadcast) involves broadcasting the latitude, longitude, altitude, velocity, identification and other information from on-board systems. Any suitable receiver may receive and process these broadcasted messages, which can be an ADS-B Ground Station which processes the ADS-B messages and generates aircraft reports to be used by Air Traffic Controllers.

To improve the efficiency, safety, and capacity of air space system, an Automatic Dependent Surveillance-Broadcast (ADS-B) is one of the popular technologies used in air traffic surveillance.The ADS-B uses 1090 MHz band.ADS-B is complemented by existing radar-based technologies to locate aircraft.The coexistence of radar systems and ADS-B is a key system to detect and resolve conflicts in the Next Generation Air Transportation System (NGATS).But, the major disadvantage of ADS-B is its implementation complexity and increase in cost without user-friendly.This paper focuses to reduce the complexity and cost of ADS-B system implementation in MATLAB with the help of Software Defined Radio (SDR).SDR is user-friendly and easy to handle aircraft information without increasing the cost.The ADS-B system implemented with SDR can receive the multiple numbers of aircraft information such as altitude, latitude, longitude, speed, and direction in real-time.Usage of SDR maximizes the information coverage with reliability and can achieve timely communication in Air Traffic Control (ATC) networks.

Millions of small Unmanned Aerial Systems (sUAS), or drones weighing less than 55 pounds, will fly in urban airspaces within a decade. This is in addition to goals for increased Urban Air Mobility (UAM): larger transportation UAS and piloted air vehicles, including air taxi service and innovative aviation designs to revolutionize transportation. A significant problem is the lack of current management systems for this extremely large volume of air traffic, composed of heterogeneous drone shapes, sizes, and onboard equipment capabilities, flying adjacent to larger UAM vehicles in spaces previously unoccupied by General Aviation (GA). Robust and resilient detection, identification, localization, and tracking of sUAS sharing UAM airspace is complicated by urban factors such as non-transmitting, non-cooperative drones. Exacerbating these challenges, current technological limitations and vulnerabilities in Global Positioning System (GPS), Automatic Dependent Surveillance-Broadcast (ADS-B), and Inertial Navigation Systems (INS) can pose safety and security threats. To streamline a vision of safe and secure sUAS-UAM shared airspace, we propose Drone Net, a UAS Traffic Management (UTM) network of multi-modal ground and flight instruments. Drone Net is an architecture fusing a network of passive visual and acoustic sensor nodes with active Radio Detection and Ranging (radar) and Light Detection and Ranging (lidar) sensing methods for UTM, designed for integration with existing Air Traffic Control (ATC) and future UAM systems. The purpose of the Drone Net system is to evaluate use of Electro-Optical/Infrared (EO/IR) and acoustic arrays networked within an urban UAS operating region such as uncontrolled Class-G and waiver-granted Class-D airspace. The Drone Net approach combines detection, tracking, and localization estimation from radar, ADS-B, and EO/IR such that the design is robust to sensor errors, sample loss, and spoofing or other types of attacks. The system experimental design allows for emulation of corrupted ADS-B, GPS, and INS data on our flight platform including capability to communicate with ground radar and EO/IR to recover from flight instrument major and minor malfunctions such that a Drone Net cooperative UAS can be engineered to be fail-safe and fail-secure. We hypothesize that the Drone Net network of rooftop sensors, shown below, provides this conceptualized fail-safe, fail-secure property based upon the combination of self-localization with backup and confirming data from the ground sensor network. Further, with ground-system sensor fusion as well as UTM flight plan and registration information fusion, the overall system can manage small UAS that are both compliant and non-compliant alongside GA and UAM more safely than a single mode like ADS-B alone. To test our hypothesis, we envision two experiments this year. First, a test to confirm that we can emulate ADS-B, GPS, and INS sensor data corruption, leading to recovery using backup flight (lidar, EO/IR) or ground (radar, EO/IR) data to safely land an ALTA6 or other test UAS. Second, a series of Sense-and-Avoid (SAA) experiments between our test UAS and a tethered aerial obstacle. In the future, we will use this experience with fail-safe, fail-secure methods and software to further test more advanced scenarios between multiple UAS. The network of Drone Net instruments in a local area as well as regional and more global cloud-based networks will allow for heterogeneous information fusion and algorithm development for multi-sensor drone detection, classification, and identification with more accuracy than a single database or sensor system. The latent power of the Drone Net project is in its open-design ground and flight sensor network with data sharing capability to improve data mining and machine learning over time for analysis and security applications. More concrete applications for Drone Net include UTM integration with ATC and UAM, but also airspace safety and security for campus and public venues in general. Herein, we will present our experimental design and current test data from Embry-Riddle Aeronautical University in collaboration with University of Colorado Boulder toward completing the open specification for ground and flight instruments. We would additionally like to invite others to participate in growing the network and the data available for UTM, UAM, and GA shared airspace research.

This paper designs, simulates, and tests a potential Automatic Dependent Surveillance-Broadcast (ADS-B) space-oriented message set to improve situational awareness of commercial space vehicles inside the National Airspace System (NAS), and to minimize their impacts and potential hazards on the NAS. ADS-B is considered as the solution to integrate the future commercial space transportation system with the air transportation system. To accommodate future space flight operations in the NAS, a potential ADS-B space-oriented message set is proposed to be exclusively transmitted from space vehicles to other traffic and air traffic controllers. New data fields are defined in the message set to cover a space vehicle's entire flight profile. The formats of these new data fields are demonstrated in details. A simulation is created containing space vehicle and aircraft trajectories to test the functionality of the ADS-B space-oriented message set. The message set is encoded at the space vehicle site, transmitted from space vehicle to aircraft via the Universal Access Transceiver (UAT) datalink, and decoded at the aircraft site. The simulation eventually reaches a conflict scenario. By using the Closest Point of Approach (CPA) algorithm, the aircraft analyzes its own state vector and the space vehicle's state vector decoded from ADS-B messages to perform conflict detection. Sensitivity studies are conducted based on the CPA algorithm concentrating on three ADS-B system parameters, which are message update rate, data latency, and state vector accuracy.

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

This work presents a risk assessment methodology, preliminary proposed in [1], which is the fusion of the absolute and the relative risk assessment methods adopted by the International Civil Aviation Organization. The proposed methodology uses the Fluid Stochastic Petri Net (FSPN) as modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed and the legacy system models. It was applied to assess the safety properties of a new air traffic surveillance concept, named automatic dependent surveillance - broadcasting (ADS-B). As conclusions, the proposed methodology assured to assess the safety properties of systems based on the current safety critical system paradigm - especially concerning the air transportation system. Besides, the FSPN formalism provided important modeling capabilities and discrete event simulation allowing estimating the desired safety metrics. Finally, the ADS-B (proposed system) has significantly reduced the risks of separation losses between aircrafts if compared to the usual surveillance radar systems (legacy system) in air traffic control (ATC) environment.

Application layer interoperability between the surveillance broadcast services system (SBSS) and automatic dependent surveillance - broadcast (ADS-B) avionics is a critical requirement for the next generation air transportation system (NextGen). Demonstrating compatibility between the SBSS and avionics requires the integration of diverse avionics tools, simulated environments tools, RF transmitter test sets, signal analyzers, SBSS equipment, and other receiving systems. ITT has developed a testbed that enables not only validation of the SBSS requirements and RTCA standards, but also provides a window into the user's perspective for various applications. The RF transmitter test set is particularly valuable for generating simulated aircraft flight patterns because it can produce 1090, UAT, and 1030 messages with dynamically programmable content. These ADS-B, Mode S, and ATCRBS messages stimulate SBSS behavior, resulting in transmissions that affect the information and system states held by avionics and air traffic control. A series of simulations with the SBSS and avionics in the loop are conducted and subsequently analyzed.

The US Federal Aviation Administration is proposing an upgrade to air transportation that will fundamentally overhaul the current, aging system. A key component, the automatic dependent surveillance broadcast (ADS-B) system, will enhance air traffic monitoring and control by requiring aircraft to continually broadcast position, identity and velocity via unencrypted data links to ground stations. Although ADS-B may enhance air traffic safety and support the increase in traffic demands, open broadcast of clear aircraft data points raise serious security concerns. The ability to encrypt ADS-B message transactions would afford protection to ensure that the confidentiality of aircraft data is not compromised. The implementation of an encryption framework for a large, distributed and dynamic system, however, is nontrivial. This paper examines encryption schemes and highlights challenges associated with implementing confidentiality security protections for the ADS-B environment.

One of the main values of utilizing automatic dependent surveillance - broadcast (ADS-B) data for air traffic control is that it provides greatly improved coverage as well as improved accuracy. As with all technology advances and deployments, especially in the National Airspace System (NAS) domain, there is a long transition time when the old and new systems must work together. The goal of the virtual radar is to provide ADS-B data in a way that completely emulates the characteristics of the current physical radars such that any automation system receiving the data will not have to be modified. Some of the issues that must be addressed include accuracy differences, conversion from cartesian GPS coordinates to polar range-azimuth coordinates, update frequency, providing a conversion of the of the ADS-B data to common digitizer (CD) beacon messages, generating the beacon real time quality control (BRTQC) and search real time quality control (SRTQC) messages as well as the radar status messages. Update frequency has unique issues to be resolved in the fact that the timing of the ADS-B reports may not correspond with the time that virtual radar beam may have hit the target. This issue of time registration will be investigated and the approaches to solving them discussed. The test and validation of virtual radars may require some new procedures and test tools to adequately insure the accuracy and correct operation. The benefits of virtual radars are exciting as they allow all of the benefits of ADS-B, improved coverage, and accuracy, and less maintenance without having to wait for upgraded automation systems.

ADS-B (Automatic Dependent Surveillance— Broadcast) is an emerging means of aeronautical surveillance for air traffic control (ATC) where aircraft periodically report their positions to the ground. Although ADS-B can provide a better positional accuracy and update rate, anomaly position report has been concerned. Therefore, the reported positions should be verified at the ground before being provided to ATC applications. This paper proposes a position verification method combining angle-of-arrival (AOA) and time-difference-of-arrival (TDOA). The proposed method was evaluated by numerical simulations. As a result, reduction of miss detections was observed.

The global positioning system (GPS) is the core element of the next-generation communication, navigation, surveillance, and air traffic management (CNS/ATM) system. However, GPS signals are vulnerable to radio-frequency interference (RFI), which can significantly impact the normal operation of the CNS/ATM system. In order to maintain CNS/ATM system operation during GPS outages and to meet safety requirements, an alternative positioning, navigation and timing (APNT) based on a radio link of the automatic dependent surveillance-broadcast (ADS-B) can be used. This study first evaluates two navigation algorithms for an ADS-B radio link, and the real aircraft ADS-B data collected at the civil aviation authorized ground stations are used to evaluate the positioning performance of the proposed backup aviation navigation and surveillance system. In addition, the main factor affecting the positioning performance of the radio navigation system is the geometric distribution of ground stations. Therefore, the geometric distribution of the actual ADS-B ground stations in the CNS/ATM system is evaluated using horizontal dilution of precision for a specific flight information region. Overall, the results of the actual flight data show that it is highly feasible to apply the ADS-B radio link as an APNT solution.