# Combating Fake News with Cryptography in Quantum Era with Post-Quantum Verifiable Image Proofs
## 7 Secure Image Provenance with C2 PA: Embedded Signing, Threat Models, and Defenses  
The Coalition for Content Provenance and Authenticity (C2 PA) provides a framework for ensuring the authenticity of digital images by embedding cryptographic signatures into the content at the time of capture. A key component of this framework is the embedded signing key, which is unique to each camera. During manufacturing, the camera generates a signing key on-device, and this key is certified by a C2 PA authority. This process establishes a root of trust in the camera and its signing key, ensuring that only the camera is trusted to sign images, while editors and other third parties are not. The secure signing process involves the camera signing the raw RGB values and metadata (e.g., location, timestamp, exposure time) at the moment an image is captured. This signature binds the image data to its metadata, creating a tamper-evident record of the image's provenance. The signed image can then be verified by anyone with access to the camera's public key, ensuring that the image has not been altered, since it was captured. The threat model assumes that an attacker has access to the camera and its public key but cannot extract the private signing key or force the camera to sign fabricated images. This model is designed to protect against malicious actors who may attempt to manipulate or forge images, while maintaining the integrity of the signing process. The root of trust lies solely in the camera and its signing key, meaning that no other entity, including editors, is trusted to sign or modify images. The verification goal of C2 PA is to ensure that an edited photo results from acceptable transformations applied to a C2 PA-signed image. This requires verifying both the authenticity of the original image and the integrity of the editing process. However, achieving this goal is not without challenges, as several potential attacks must be mitigated. One such attack is the key extraction attack, where an attacker attempts to extract the camera's private signing key. To defend against this, cameras are equipped with Hardware Trusted Execution Environments (TEEs), which protect the signing key from unauthorized access. Additionally, if a key is compromised, it can be revoked by the C2 PA authority, preventing further misuse. Another attack is the picture-of-picture attack, where an AI-generated image is displayed on a screen and re-photographed by a camera. This attack can be detected through metadata analysis, such as identifying inconsistencies in focal length or other camera settings that would not match a genuine capture. Metadata-based defenses are critical for distinguishing between authentic and re-photographed images. Semantic manipulation is another concern, where edits, such as cropping or removing elements from an image, alter its meaning. For example, removing a person from a group photo could change the narrative conveyed by the image. While C2 PA can verify that an image has been edited, it cannot inherently detect or prevent semantic manipulation. This highlights the need for additional safeguards, such as human oversight or AI-based content analysis, to address these types of attacks. Privacy risks also arise from the use of camera signatures, as they could expose the identity of the device or user. To mitigate this, group signatures can be employed, allowing multiple cameras to share a single public key, while maintaining individual private keys. This approach anonymizes the source of the image, while still enabling the verification of its authenticity. While C2 PA represents a crucial step forward in image provenance, it must be combined with additional security measures to address evolving threats. The framework provides a strong foundation for ensuring the authenticity and integrity of digital images, but ongoing innovation and collaboration are needed to stay ahead of sophisticated attacks.