Quantum cryptanalysis using digital ant in pervasive environment
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
Nowadays security is providing essential provision to prevent unauthorized or illegal access. It has become an essential part of every framework in electronic age. In the present scenario as the world data in increasing exponentially-with time interval, there is an increased threat of malicious data. Hence, security becomes the vital component to make this growing electronic usage leds to a sustainable development in society. Swarm intelligence is an upcoming field; through its stochastic behavior it has the capabilities to solve a greater range of optimization problem. Using the property of Meta heuristic techniques of finding the most optimized solution authors attempted to use them for security purposes. Paper discusses about an agent based meta heuristic based approach to develop cyber defense mechanism where a team of human and software ants mitigate security threat posed in a pervasive environment. The DigitalAnts™ system architecture will wander through entire network in identifying the invaders i.e. viruses, trojan horses etc. Also, the quantum theory is used to generate the polynomial data analogous to pheromone in Ant Colony Optimization.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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