Secure communication using a chaos based signal encryption scheme
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
The large-scale proliferation of wireless communications both inside and outside the home-office environment has led to an increased demand for effective and cheap encryption schemes. Now a new chaos based signal encryption scheme is proposed to transmit digital information signals by using the conventional synchronization of chaos and digital encryption approaches. In this scheme, either a chaotic or hyperchaotic system is used to generate a digital key after thresholding a chaotic signal. This signal along with the information digital signal is used to generate the encrypted signal. Then the encrypted signal is masked by one of the chaotic signals of the transmitter and is transmitted through the channel to the receiver as well as used to drive the transmitter chaotic system using the concept of self-modulation. At the receiver end, a suitable feedback loop is constructed for unmasking and then the decryption rule is used to recover the information signal. By suitable combinations of the chaotic signals, the effect of additional nonlinear-keys has also been considered. The effect of typical perturbing factors, like channel noise and parameter mismatch, are included and their corresponding performance analysis is discussed. By considering an appropriate circuit configuration, simulation results are presented.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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