Hybrid Cryptosystem Algorithm Vigenere Cipher and Base64 for Text Message Security Utilizing Least Significant Bit (LSB) Steganography as Insert into Image
Bibliographic record
Abstract
Security message text is aspect important in modern communications for guard privacy and confidentiality information. Without exists guarantee security, of course just can raises risk when sensitive and valuable information are accessed by unauthorized persons responsible answer. Cryptography and steganography is two field used in a manner wide For reach objective this. Algorithm Vigenere Cipher and Base64 are method used for encryption message text and Least Significant Bit (LSB) steganography was used as method for insert message encrypted to in image. LSB makes use of the last bits from pixels image for keep information addition without bother image visual display in a manner significant. With utilise method here, order encrypted can hidden in a manner confidential in image that looks normal. This hybrid cryptosystem combine excess from third algorithm such, ie speed and effectiveness encryption use algorithm Vigenere Cipher as well ability Base64 characteristics, and levels security message more increase.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".