KEAMANAN CITRA DIGITAL DENGAN MEMANFAATKAN PROSES PENERAPAN ALGORITMA DATA ENCRYPTION STANDART (DES) PADA EKTRAKSI PIXEL
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In today's digital technology, almost all activities can be documented in the form of digital images. The problem that arises is that images that are confidential can be stolen and accessed by people who are not entitled. To overcome this security problem, image files can be encrypted using cryptographic algorithms. One cryptographic algorithm that can be used is the Data Encryption Standard (DES) algorithm. This algorithm is a block cipher with a size of 64 bits or 8 bytes. Therefore, DES is used to encrypt image files per 8 bytes. Each encryption process will pass 16 cycles and produce cipher bytes. The result of encryption is an image file with an unrecognized format and cannot be opened because the contents of the byte file have been randomized. To return the scrambled file back to the original image file, perform the decryption process using the same key as the encryption key. The application can be used to encrypt and decrypt images using the DES algorithm. The application can also display the steps of the encryption and decryption process towards the contents of the byte in the file.
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.
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 | 0.003 | 0.014 |
| Open science | 0.004 | 0.002 |
| 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