Number of Pixel Change Rate and Unified Average Changing Intensity for Sensitivity Analysis of Encrypted inSAR Interferogram
Bibliographic record
Abstract
The transmission of images from satellites to earth is on the brink of many threats which can affect the confidentiality of the data as well as its quality. Several encryption algorithms are used to secure the transmitted images. The objective in this work is to analyze the sensitivity of a particular type of satellite image, which is an interferogram from interferometric imaging systems inSAR system. This image is encrypted by cryptosystem based on the Advanced Encryption Standard with key length of 256 bits (AES-256) standard and the asymmetric Rivest, Shamir & Adelman (RSA) encryption algorithm using Counter-mode encryption (CTR) mode and Output FeedBack (OFB) mode. The analysis made in this paper is carried out on two types of sensitivity. The first analysis is the sensitivity to change of a pixel in the original interferogram and the second is the sensitivity to the key. Two parameters are used to assess sensitivity: The Number of Pixel Change Rate (NPCR) and the Unified Average Changing Intensity (UACI). The obtained results show that the two modes AES-256-OFB and AES-256-CTR are favorable but cannot be implemented on board a satellite without providing a mechanism capable of compensating for the low resistance to error propagation. Metrics on the clear and encrypted interferogram are exploited such as the Structural Similarity Index (SSIM), Gradient-based Structural Similarity (GSSIM), The use of these metrics, allowed us to see that a change of one pixel in the interferogram and the change of the encryption key will affect the quality of the interferogram, as well as a statistical histogram analysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".