IRS-UAV Assisted Secure Integrated Sensing and Communication
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
Thanks to its concurrent and dual functions, integrated sensing and communication (ISAC) has been considered as a promising technology for 6G networks. However, ISAC systems may suffer from security threats due to the broadcast nature of wireless channels. By combining the maneuverability of unmanned aerial vehicle (UAV) and the propagation environment reconfiguration capability of intelligent reflecting surface (IRS), the security challenges of ISAC can be effectively addressed. In this article, we first outline the advantages that IRS-UAV may bring to the ISAC, and introduce several typical security techniques. Then, we propose two security schemes for IRS-UAV enabled ISAC to deal with the jamming and eavesdropping attacks, respectively. In the anti-jamming design, deploying IRS-UAV can provide a line-of-sight link for the blocked target and leverage the passive beamforming to fight against the malicious jammer. Furthermore, the aerial IRS can coordinate artificial noise to ensure the accuracy of target sensing while suppressing eavesdropping. Numerical results are presented to verify the effectiveness of the proposed schemes. Finally, future challenges in this direction are outlined.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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