Analytical and Simulation Based Evaluation of Wireless-to-Wireline TCP-SYN Attacks
Bibliographic record
Abstract
Denial of service (DoS) attacks present a serious threat to the entire Internet community, as they are very easy to implement, and yet they have the ability bring any arbitrary networked-computer to their knees by flooding them with useless traffic. Although the current volume of published research works on DoS appears significant, most of these works share two common limitations. The goal of this paper is to overcome the limitations of the previous research works on DoS, through analytical and simulation-based evaluations of one particular type of DoS attack-TCP-SYN flooding attack. In the first part of the paper, the general concept of wireless-to-wireline DoS attacks is introduced, and the unique challenges associated with this type of attack are outlined. Subsequently, a theoretical analysis concerning the actual ability of a single mobile user to stall one of three major types of Internet servers using a TCP-SYN DoS attack is presented. The results of this analysis show that TCP-SYN attacks launched from either of the existing mobile-wireless systems can stall all three types of Internet servers, and therefore they do pose a real threat to the Internet community. Nevertheless, the initiators of these attacks should not expect to remain hidden or unpunished, as the stream of forged TCP-SYN packets can effectively be traced back to the source. In the second part of the paper, a Qualnet-based simulation model for the analysis of wireless-to-wireline TCP-SYN attacks is presented. Through a series of experimental results obtained using the given model, the conclusions outlined in the first part of the paper are verified
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".