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Record W2584926063 · doi:10.1109/glocom.2016.7842142

Physical Layer Secure Information Exchange Protocol for MIMO Ad Hoc Networks against Passive Attacks

2016· article· en· W2584926063 on OpenAlexaff
Qiao Liu, Guang Gong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkPhysical layerRelayMIMOWireless ad hoc networkChannel (broadcasting)Transmission (telecommunications)Protocol (science)CryptographyRelay channelComputer securityWirelessTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we propose a secure transmission protocol for two users exchanging their respective information in an n-hop MIMO Ad hoc network. By exploiting the properties of the transmission medium in the physical layer, three channel models are utilized to provide secure transmission, namely one-way relay channel, two-way untrusted relay channel, and multiple access channel. Using these channel models, we design a basic protocol with a minimized time slot cost, i.e. n+1. Based on this basic protocol, we show that the attacker, either untrusted relay or external eavesdropper, can only obtain a summed signal in each time slot, and this summed signal cannot be decomposed to recover the individual information from the users. We then present cryptographic analysis for the first time to identify a weakness which is common for all known security schemes based on the summed signal. Thirdly, we introduce an evolutionary protocol proposed with two rounds of interlaced information exchange, which defeats this weakness. Finally, the simulation is performed to demonstrate the theoretical analysis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.290
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

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