A layered security architecture based on cyber kill chain against advanced persistent threats
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
Inherently, static traditional defense mechanisms which mostly act successfully in detecting known attacks using techniques such as blacklisting and malware signature detection are insufficient in defending against dynamic and sophisticated advanced persistent threat (APT) cyberattacks. These attacks are usually conducted dynamically in several stages and may use different attack paths simultaneously to accomplish their commission. Cyber kill chain (CKC) framework provides a model for all stages of an intrusion from early reconnaissance to actions on objectives when the attacker's goal is met which could be stealing data, disrupting operations or destroying infrastructure. Achieving the final goal, an adversary must progress all stages successfully. Any disruption at any stage of the attack by the defender would mitigate or cease the intrusion campaign. In this chapter, we align 7D defense model with CKC steps to develop a layered architecture to detected APT actors tactics, techniques and procedures in each step of CKC. This model can be applied by defenders to plan resilient defense and mitigation strategies against prospective APT actors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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