Cyber defence triage for multimedia data intelligence: Hellsing, Desert Falcons and Lotus Blossom APT campaigns as case studies
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
Advanced persistent threats (APTs) refer to sophisticated attacks to businesses and individuals in which adversaries use multiple attack vectors to achieve their objectives. The main challenge regarding APT analysis and defence is that all research body about APTs is fragmented; only a few scientific papers have discussed APT features. In order to defend against APTs, it is necessary to have a complete understanding of their tactics, techniques, and procedures (TTPs). In this paper, we analyse TTPs of three APT groups, namely Hellsing, Desert Falcons and Lotus Blossom, that actively targeted multimedia data storage and multimedia systems. Adopting three attack attribution models (i.e., Lockheed Martin cyber kill-chain, diamond model and course of action matrix) we provide a comprehensive cyber defence triage process (CDTP) against the considered APTs. The CDTP highlights steps undertaken by these APT groups, uncovers factors that have influenced achieving their objectives and suggests possible mitigations against them.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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