Media Integrity and Authentication: Status, Directions, and Futures

We provide background on emerging challenges and future directions with media integrity and
authentication methods, focusing on distinguishing AI-generated media from authentic content
captured by cameras and microphones. We evaluate several approaches, including provenance,
watermarking, and fingerprinting. After defining each method, we analyze three representative
technologies: cryptographically secured provenance, imperceptible watermarking, and soft-hash
fingerprinting. We analyze how these tools operate across modalities and evaluate relevant threat
models, attack categories, and real-world workflows spanning capture, editing, distribution, and
verification. We consider sociotechnical “reversal” attacks that can invert integrity signals, making
authentic content appear synthetic and vice versa, highlighting the value of verification systems
that are resilient to both technical and psychosocial manipulation. Finally, we outline techniques
for delivering high-confidence provenance authentication, including directions for strengthening
edge-device security using secure enclaves.