Detecting intrusions specified in a software specification language
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
To protect software against malicious activities, organizations are required to monitor security breaches. Intrusion detection systems (IDS) are those kinds of monitoring tools that have gained a considerable amount of popularity, A number of specification-based IDSs have been proposed, where security requirements or attack scenarios are specified using some languages. Currently, attack specification languages are being deployed for describing security requirements. Use of two different languages for software specification and security specification invites a number of unwanted but complicated issues, such as duplication of requirements specification effort as well as the existence of redundant and conflicting requirements. In this paper, we present an intrusion detection technique that uses a formal software specification language called abstract state machine language (AsmL) for the specification of security requirements. We present a framework, and develop the algorithm for the IDS that interprets the AsmL attack scenario specifications in order to detect intrusions. Moreover, we discuss case studies where the presented intrusion detection system is used to detect attacks.
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 | 0.000 | 0.001 |
| Open science | 0.000 | 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