Application of Simple Power Analysis to Stream Ciphers Constructed Using Feedback Shift Registers
Why this work is in the frame
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Bibliographic record
Abstract
Although power analysis attacks have been extensively applied to block ciphers, only limited research has been done to analyze their effectiveness on stream cipher hardware implementations. In this paper, we investigate methods of simple power analysis applied to stream ciphers based on multiple feedback shift registers (FSRs) and demonstrate the effectiveness of the methods by examining the cipher Grain which involves both a linear and a nonlinear FSR. A divide-and-conquer attack is presented where the attacker guesses the bit values of the FSRs independently and then checks the correctness of the guess using information derived from measured power consumption of the cipher core. Experimental results of the attack applied to simulated power data obtained for a CMOS implementation of Grain show that it is possible to recover directly the cipher state using only about 3000 power samples. For ciphers constructed using a general architecture of multiple FSRs, the attack has the potential to be successful with a complexity substantially less than exhaustive key search.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it