Study of Different Types of Attacks on Multicast in Mobile Ad Hoc Networks
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
Security is an essential requirement in mobile ad hoc networks (MANETs). Compared to wired networks, MANETs are more vulnerable to security attacks due to the lack of a trusted centralized authority, easy eavesdropping, dynamic network topology, and limited resources. The security issue of MANETs in group communications is even more challenging because of the involvement of multiple senders and multiple receivers. In this paper, we present a simulationbased study of the impacts of different types of attacks on mesh-based multicast in MANETs. We consider the most common types of attacks, namely rushing attack, blackhole attack, neighbor attack and jellyfish attack. Specifically we study how the processing delay of legitimate nodes, the number of attackers and their positions affect the performance metrics of a multicast session such as packet delivery ratio, throughput, end-to-end delay, and delay jitter. To the best of our knowledge, this is the first paper that studies the vulnerability and the performance of multicast in MANETs under various security threats.
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.
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 it