Advancing Whistleblower Protection Science
Our research drives innovation in blockchain-based evidence management, AI-powered deepfake detection, steganographic communication, and environmental crime analytics. Explore our key research areas and publications.
Developing neural network architectures for detecting manipulated images, videos, and audio evidence submitted to the platform.
Researching immutable evidence chains, smart contract verification, and decentralized consensus mechanisms for whistleblower data integrity.
Building tools for metadata analysis, evidence authentication, and chain-of-custody tracking that meet legal admissibility standards.
Applying statistical models and machine learning to identify environmental crime patterns, predict hotspots, and measure intervention effectiveness.
Designing zero-knowledge proof systems, anonymous credential frameworks, and steganographic channels for secure whistleblower communication.
Researching edge computing, anomaly detection algorithms, and distributed sensor networks for real-time environmental monitoring.
Recent Publications
BEACONSAFE: A Blockchain-Enhanced Environmental Crime Reporting Platform
2026Comprehensive system design paper covering architecture, security model, and evaluation of the BEACONSAFE ecosystem.
Deepfake Detection in Environmental Crime Evidence
2025Novel approach to detecting manipulated multimedia evidence using multi-modal neural network analysis.
Steganographic Channels for Whistleblower Protection
2025Research on covert communication methods enabling safe information exchange under surveillance conditions.