ADS-B and AIS Spoofing Detection for Science Fair

ISEF Category: Embedded Systems

Subcategory: Networking and Data Communications  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

A plane or ship can say it is one place while its radio signal says something else. That mismatch is the clue your project can catch. You are building a system that listens, compares, and flags suspicious position data. That is the same basic idea behind a lot of real-world signal security work.

What Is It?

ADS-B and AIS are broadcast systems. Aircraft use ADS-B, and ships use AIS. Each one sends out identity and position data so others can track movement. A receiver with an RTL-SDR and a Raspberry Pi can collect those signals and turn them into a stream of positions.

Your project asks a simple question, can the reported position be trusted? One way to check is multilateration, which means using signal arrival times or bearings from several receivers to estimate where the transmitter really is. Think of it like hearing a loud clap from several places at once. If each listener marks the sound on a map, the overlap points to the source. When the broadcast position and the network-based estimate disagree, you may have spoofing, bad data, or another anomaly.

This topic sits at the edge of radio engineering, networking, and data analysis. You do not need to invent a new receiver from scratch. You need to design a pipeline that captures signals, cleans them, compares two position estimates, and decides when they disagree enough to matter.

Why This Is a Good Topic

This is a strong science fair topic because you can test a clear signal-security problem with measurable data. The core idea, comparing self-reported location with network-derived location, is easy to state and hard to fake. That gives you room to study detection thresholds, receiver spacing, timing error, and false alarms. You can learn SDR basics, time synchronization, data cleaning, and anomaly detection, all skills that map to real communications research.

Research Questions

• How does receiver spacing affect the accuracy of multilateration-based spoofing detection?
• What is the effect of timing synchronization error on false spoofing alerts?
• Does combining ADS-B and AIS data improve detection of inconsistent position reports?
• To what extent does signal strength filtering reduce bad position estimates?
• Which anomaly threshold best separates normal track noise from likely spoofing?
• How does the number of receivers in the network change detection confidence?

Basic Materials

• RTL-SDR USB receiver or similar SDR dongle.
• Raspberry Pi or laptop with Linux support.
• Antenna suitable for ADS-B or AIS frequencies.
• Internet access for software setup and data logging.
• External hard drive or cloud storage for captured signal files.
• Spreadsheet software for track comparison and plotting.
• Map data or open street map tiles for visual checks.
• GPS-disciplined time source or a network time sync tool, if available.

Advanced Materials

• Multiple RTL-SDR receivers for a small distributed network.
• Raspberry Pi units or small computers at each receiver site.
• Antennas tuned for ADS-B and AIS bands.
• GPS-disciplined oscillator or precise time synchronization hardware.
• Band-pass filters for cleaner signal capture.
• Low-noise amplifier for weak-signal environments.
• Server or workstation for central fusion and comparison.
• SDR analysis tools for offline decoding and multilateration testing.

Software & Tools

• dump1090: Decodes ADS-B messages and produces track data for aircraft monitoring.
• GNU Radio: Builds and tests custom radio signal-processing blocks for receiver experiments.
• QtMMS or similar AIS decoder: Turns marine radio packets into usable ship track data.
• Python: Cleans tracks, compares positions, and calculates error metrics.
• QGIS: Maps reported and estimated positions so you can spot mismatches visually.

Experiment Steps

1. Define the spoofing signal you want to detect, such as a large mismatch between broadcast position and multilateration estimate.
2. Choose the receiver layout you can support, then map where each receiver will sit and what timing data you can trust.
3. Design a data pipeline that decodes messages, time-stamps them, and stores track history for later comparison.
4. Build a comparison method that turns location disagreement into a single alert score with a threshold you can test.
5. Plan controls that separate true anomalies from normal noise, reception loss, and reflection errors.
6. Decide how you will validate the system with known-good tracks, simulated offsets, or archived public datasets.

Common Pitfalls

• Comparing track points without accounting for receiver clock drift, which can make the multilateration estimate look wrong.
• Mixing ADS-B and AIS records without separating their different update rates and coverage patterns, which breaks the analysis.
• Using only one or two receivers, which leaves you without enough geometry to localize the source well.
• Treating every position mismatch as spoofing, which creates false alarms from weak signals, reflections, or decode errors.
• Plotting raw coordinates before cleaning duplicate packets and outliers, which hides the real error pattern.

What Makes This Competitive

A stronger project goes past a simple mismatch detector. You can test several receiver layouts, compare more than one anomaly metric, and measure how often each method raises false alarms. You can also separate spoofing-like behavior from ordinary GPS jitter, multipath reflections, and packet loss. That kind of careful evaluation makes the work feel like a real systems study, not just a demo.

Project Variations

• Use archived ADS-B flight data and simulate position offsets to test how well your detector catches fake jumps.
• Focus on AIS near a harbor and compare ship tracks against shore-based multilateration estimates from multiple receivers.
• Compare simple threshold detection with a machine learning classifier that uses track speed, heading change, and position error as inputs.

Learn More

• NIH PubMed: Search review articles on ADS-B spoofing, AIS security, and radio-based anomaly detection for background reading.
• NOAA Coast Survey: Explore marine navigation and AIS-related resources to understand how ship position data is used.
• NASA Earthdata: Search for remote sensing and positioning articles that explain track validation and geospatial comparison.
• GNU Radio Documentation: Learn the open-source signal-processing blocks used in SDR pipelines and receiver experiments.
• MIT OpenCourseWare: Search for courses on digital communication, signal processing, and wireless networking for free lecture material.