Multi-Objectives Model to Process Security Risk Assessment Based on AHP-PSO
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 the security risk assessment play a crucial role, which is applied to the entire life cycle of information systems and communication technologies but still so many models for security risk assessment are non practical, therefore, it should be measured and improved. In this paper, a novel approach, in which Analytic Hierarchy Process (AHP) and Particles Swarm Optimization (PSO) can be combined with some changes, is presented. The method consists of; firstly, the analytic hierarchy structure of the risk assessment is constructed and the method of PSO comprehensive judgment is improved according to the actual condition of the information security. Secondly, the risk degree put forward is PSO estimation of the risk probability, the risk impact severity and risk uncontrollability. Finally, it gives examples to prove that this method Multi Objectives Programming Methodology (MOPM) can be well applied to security risk assessment and provides reasonable data for constituting the risk control strategy of the information systems security. Based on the risk assessment results, the targeted safety measures are taken, and the risk is transferred and reduced, which is controlled within an acceptable range.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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