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Pontifical Catholic University of Rio de Janeiro

Academic institutionsouthamerica · br
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Research library119linked papers
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Selected work

Representative Papers

Enhanced Multiuser CSI-Based Physical Layer Authentication Based on Information Reconciliation

Feb 01, 2025IEEE Wireless Communications Letters

To address the insufficient robustness and excessive overhead of physical-layer authentication in low-power IoT multi-user scenarios, this paper proposes a channel state information (CSI)-based information reconciliation authentication scheme. The method innovatively incorporates the Slepian–Wolf distributed source coding principle into a time-varying multi-user CSI authentication framework, integrating adaptive quantization with polar codes to achieve efficient, low-overhead information reconciliation. Temporal alignment of multi-user channel measurements and variable-bit quantization further enhance authentication consistency and interference resilience. Experimental results demonstrate a detection probability exceeding 99.80% at an extremely low false alarm rate (<10⁻⁴), significantly outperforming existing approaches. This work establishes a new paradigm for highly reliable, cost-effective physical-layer authentication tailored to resource-constrained IoT deployments.

1 citationsRead paper

Towards Polyglot Data Processing in Social Networks using the Hadoop-Spark Ecosystem

Jan 20, 2025Artificial Intelligence and Big Data Trends 2025

To address the challenge of processing multi-source, heterogeneous data in social networks, this paper proposes a unified batch-stream-graph analytics framework built upon the Hadoop-Spark ecosystem. The method systematically integrates Hive (for SQL-based batch processing), HBase (for low-latency key-value lookups), and GraphX (for scalable graph computation) under a single Spark execution layer. It supports three core analytical tasks: user influence assessment, high-frequency term statistics, and community relationship mining. Leveraging HDFS for distributed storage, YARN for resource orchestration, and multi-language APIs, the framework achieves loosely coupled integration of computation and storage. End-to-end experiments on real-world social datasets demonstrate that the hybrid architecture accelerates complex relational analysis by 1.8–3.2× compared to single-component baselines, significantly improving both processing efficiency and system flexibility.

1 citationsRead paper
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