ADS-B Track Spoofing Detection via Weighted Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing vulnerability of Automatic Dependent Surveillance-Broadcast (ADS-B) systems to spoofing attacks, which can generate false aircraft tracks, disrupt air traffic, and compromise safety due to unencrypted waveforms and the proliferation of affordable software-defined transmitters.
Innovation Solution
A system and method that applies a plurality of detection tests, including power level validation, ADS-B rules-based analysis, Doppler offset, multi-band detection, and antenna diversity, with weighted scoring to differentiate between valid and spoofed ADS-B tracks, optimizing detection tests and weighting factors based on environmental conditions and attack types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If unencrypted ADS-B waveforms are used for accessibility, then ease of operation is improved, but vulnerability to spoofing attacks increases
Solution Approach 1:
The system performs preliminary validation checks on ADS-B waveforms before accepting them as legitimate. Multiple detection tests are conducted in advance to verify track authenticity, including checking for proper message formatting, valid aircraft identifiers, and consistent positional data, thereby preventing spoofed tracks from being accepted into the system
Solution Approach 2:
A verification layer is introduced as an intermediary between the ADS-B waveform reception and the air traffic management system. This intermediary component applies detection tests and weighting factors to assess track legitimacy, acting as a mediator that filters out spoofed information while allowing legitimate ADS-B data to pass through
2Measurement precision
If multiple detection tests are applied to each waveform, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system changes parameters by applying different weighting factors to various detection tests based on environmental conditions and attack types. The verification unit can adjust the importance of different detection tests dynamically, allowing the system to maintain high detection accuracy while adapting to different operational scenarios without requiring a completely different system architecture
Solution Approach 2:
The detection system is designed to be dynamic, with the ability to adjust which detection tests are applied and their respective weighting factors based on current environmental conditions and suspected attack types. This dynamic approach allows the system to optimize detection precision for different scenarios without requiring maximum complexity in all situations
3Reliability
If detection tests are optimized based on environmental conditions and attack types, then reliability is improved, but adaptability decreases
Solution Approach 1:
The system prepares multiple sets of detection tests and weighting factors in advance for different environmental conditions and attack types. By having pre-configured detection strategies ready, the system can quickly switch between them based on the situation, maintaining both reliability through optimized detection and adaptability through pre-planned flexibility
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively discriminates between valid and spoofed ADS-B tracks, enhancing air traffic control by reducing the risk of spoofing attacks and ensuring accurate situational awareness, even in complex and dynamic environments.
Implementation Method 1
Doppler offset, where the apparatus compares a detected Doppler offset with velocities, headings, and/or changes thereof that are reported by the apparent ADS-B track
Implementation Method 2
power level validation, ADS-B rules-based analysis, Doppler offset, multi-band detection, and antenna diversity, with weighted scoring to differentiate between valid and spoofed ADS-B tracks
Data Source
AI summary
A method for discriminating between spoofed and valid ADS-B tracks includes applying a plurality of spoofing detection tests to an ADS-B waveform, applying weighting factors to the resulting test scores, and combining the weighted scores to obtain a confidence level indicating whether the ADS-B track is valid or spoofed. The detection tests can include power level validation, Doppler offset, ADS-B rules-based analysis, multi-band detection, track origination detection, and antenna diversity. The selection of applied detection tests and/or weighting factors can be adjusted and/or selected from corresponding libraries, according to operating conditions. Tracks can be displayed together with confidence level indications, and/or excluded from display if their confidence levels are below an adjustable threshold. Weighting factors can be chosen and/or updated by a machine learning model according to success in detecting simulated and/or actual spoofed tracks. A spoofing attack can be declared according to the number of spoofed tracks detected.