BI-MQTT: Broker-Independent Integrity for Publish–Subscribe Messaging with Ring Signatures
Bibliographic record
Abstract
Message Queuing Telemetry Transport (MQTT) is a lightweight publish-subscribe protocol widely deployed in Internet of Things (IoT) and cyber-physical systems such as smart grids, industrial automation, and healthcare. However, its reliance on centralized brokers introduces a critical trust dependency: if a broker is compromised or malicious, message integrity and unlinkability cannot be guaranteed. We propose BIMQTT, a broker-independent integrity and origin authentication extension to MQTT that integrates ring signatures into the publish-subscribe workflow. By allowing publishers to sign messages anonymously within a group, BI-MQTT enables subscribers to verify origin authenticity and integrity directly, without relying on broker trust. This preserves the lightweight architecture of MQTT while adding publisher anonymity for privacy-sensitive deployments. To demonstrate practicality, we implement BIMQTT on the widely used Eclipse Mosquitto broker and evaluate its performance under realistic conditions. Experimental results show that ring signature schemes such as RST and Shacham can be integrated into MQTT with tolerable computational and bandwidth overhead, illustrating the feasibility of strengthening MQTT security using cryptographic primitives without sacrificing deployability.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".