The Role of DNS TTL Values in Potential DDoS Attacks: What Do the Major Banks Know About It?
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
In this paper, we examine the impact of DNS TTL values on the overall user experience in accessing a web site. We demonstrate that a web-site that utilizes inappropriate DNS TTL values could experience damaging and costly consequences, especially if falling victim to a DDoS attack. Subsequently, we represent the results of our survey that has looked into the DNS TTL values of the major US and EU banks. The results of this survey show that in the world of financial institutions, the level of assets and public exposure is highly correlated with the level of sophistication in DNS (Record) management. Specifically, we show that a number of (often smaller-scale) banks choose inappropriately long DNS TTL values, creating a vulnerability that could be easily exploited by an adversary. 1.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.004 | 0.001 |
| 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