Bibliographic record
Abstract
General-purpose software specification languages are introduced to model software by providing a better understanding of their characteristics. Nevertheless, these languages may fail to model some nonfunctional requirements such as security and safety. The necessity for simplifying the specification of nonfunctional requirements led to the development of domain-specific languages (e.g., attack description languages). Attack languages are employed to specify intrusion detection related aspects like intrusion signatures, normal behavior, alert correlation, and so forth. They provide language constructs and libraries that simplify the specification of the aforementioned intrusion detection aspects. Attack languages are used heavily due to the rapid growth of computer intrusions. The current trend in software development is to develop the core functionalities of the software based on the requirements expressed in general-purpose software specification languages. Then, attack languages and other security mechanisms are used to deal with security requirements. However, using two sets of languages may result in several disadvantages such as redundant and conflicting requirements (e.g., usability vs. security). Moreover, incorporating security at the latter stages of a software life cycle is more difficult and time consuming. Many research works propose the unification and reconciliation of software engineering and security engineering in various directions. These research efforts aim to enable developers to use the current software engineering tools and techniques to specify security requirements. In this chapter, we present a study on the classification of software specification languages and discuss the current state of the art regarding attack languages. Specification languages are categorized based on their features and their main purposes. A detailed comparison among attack languages is provided. We show the example extensions of the two software specification languages to include some features of the attack languages. We believe that extending certain types of software specification languages to express security aspects like attack descriptions is a major step towards unifying software and security engineering.
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.
How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".