An Authentication Protocol for Next Generation of Constrained IoT Systems
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
With the exponential growth of connected Internet of Things (IoT) devices around the world, security protection and privacy preservation have risen to the forefront of design and development of innovative systems and services. For low-value IoT devices that identify and track billion of goods in various industries—such as radio-frequency identification (RFID) tags—this involves multiple challenges in very constrained environments. IoT devices aim to design low-cost, low-complexity infrastructure while enabling robust authentication protocols with reduced latency and energy consumption. Given these challenges, in this article, we present a new lightweight authentication protocol for IoT applications, employing an authenticated-encryption (AE) cryptosystem with associated data (AEAD). Since AEAD algorithms provide data confidentiality and message integrity simultaneously, security analysis [Real-or-Random (RoR) and Scyther] results prove the robustness of the proposed protocol against IoT threats. Furthermore, to measure the computation and communication cost, FPGA and ASIC simulations using four different AEAD candidates of National Institute of Standards and Technology (NIST) lightweight cryptography competition are executed. The implementation results [e.g., 4744 gate equivalent (GE) and 0.87-mw power] clearly show that our novel design can be applied to a wide range of constrained IoT devices complying with low-cost, lightweight, and high-speed requirements.
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 | 0.001 | 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 | 0.001 |
| 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