Methods that were once considered reliable - such as metadata analysis or visual plausibility checks - are no longer enough to prevent fraud at scale. Even AI-based forensics provides only statistical indications, not legally robust proof. The question is: what can be done?
With ImageSign, Tallence introduces a different approach: instead of proving manipulation, the goal is to make authenticity verifiable. In other words, content authentication replaces heuristic detection. By applying cryptographic principles, both the origin and integrity of an image can be secured. ImageSign is built around three core elements:
- Digital signatures and hashing: An image is uniquely signed at the moment of capture or initial import. Any subsequent modification invalidates the signature.
- Provenance data (C2PA): Origin, editing history, and device integrity are documented in a tamper-resistant manner.
- Trusted Execution Environment (TEE) & device attestation: Ensure that signatures are generated within a secure and trustworthy environment.
This makes it possible to verify whether an image can be authentic - not just whether it appears plausible.
At the same time, it will not always be feasible to rely exclusively on signed images. For third-party, unsigned content, insurers must continue to apply multi-layered forensic analysis on a case-by-case basis. ImageSign is designed to support these scenarios as well, incorporating:
- JPEG error level analysis (ELA) to detect localized manipulations
- Neural inconsistency detection (e.g., CNNs, vision transformers) for anomalies in lighting, shadows, and materials
- Metadata forensics (EXIF data, toolchains, camera profiles)
- Copy-move analysis to identify duplicated regions
- Physical plausibility checks (light sources, perspective, shadows)
- Detection of retouching based on edge and gradient anomalies