A Novel Permutation-based Hash Mode of Operation FP and the Hash Function SAMOSA
Bibliographic record
Abstract
The contribution of the paper is two-fold. First, we design a novel permutationbased hash mode of operation FP, and analyze its security. The FP mode is derived by replacing the hard-to-invert primitive of the FWP mode – designed by Nandi and Paul, and presented at Indocrypt 2010 – with an easy-to-invert permutation; since easy-to-invert permutations with good cryptographic properties are normally easier to design, and are more efficient than the hard-to-invert functions, the FP mode is more suitable in practical applications than the FWP mode. We show that any n-bit hash function that uses the FP mode is indifferentiable from a random oracle up to 2n/2 queries (up to a constant factor), if the underlying 2n-bit permutation is free from any structural weaknesses. Based on our further analysis and experiments, we conjecture that the FP mode is resistant to all non-trivial generic attacks with work less than the brute force, mainly due to its large internal state. We compare the FP mode with other permutation-based hash modes, and observe that it displays the so far best security/rate trade-off. To put this into perspective, our second contribution is a proposal for a concrete hash function SAMOSA using the new mode and the P-permutations of the SHA-3 finalist Grøstl. Based on our analysis we claim that the SAMOSA family cannot be attacked with work significantly less than the brute force. We also provide hardware implementation (FPGA) results for SAMOSA to compare it with the SHA-3 finalists. In our implementations, SAMOSA family consistently beats Grøstl, Blake and Skein in the throughput to area ratio. With more efficient underlying permutation, it seems possible to design a hash function based on the FP mode that can achieve even higher performances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".