Among the candidates for NIST's post-quantum cryptography standardization project, cryptosystems that rely on Low Rank Parity Check (LRPC) codes have interesting properties, such as a low public key size. However, the key generation phase for these cryptosystems is computationally expensive when done in constant-time, which is a security requirement on the standardization project, making it almost unusable for ephemeral key generation. We present a new constant-time algorithm for key generation on LRPC code-based cryptosystems, that divides the computational costs by four when compared to previous work over ROLLO, one of the NIST candidates. Our improvement consists in changing the way objects of a quotient ring are represented. By switching from a canonical basis to an optimal normal basis, we enable the full potential of the Itoh-Tsuiji algorithm for field inversion.

Supply chain management is critical in industrial efforts to reduce costs and time, stabilize product supply, and improve profitability. Surveillance cameras play a significant role in supply chain management, as they can record work activities to achieve appropriate monitoring of company operations. A solution for ensuring the reliability of the video taken by a surveillance camera is to achieve data integrity using a cryptographic algorithm. Another important solution is the identification of a surveillance camera to ensure the traceability of video. This paper proposes a novel approach for video-based fingerprint extraction and key generation, that can be used for camera PUF construction. Our experiment shows that a 256-bit key can be extracted from 50 frames of a normal video with a resolution of 800 X 600 pixels, and we theoretically prove that our methodology satisfies the randomness, uniqueness, steadiness, and unpredictability requirements. Our PUF construction can thus be used to identify a surveillance camera from a video.