Develops a quantitative foundation for BLE flooding attack impacts on IoT and proposes an agility-based deterrence strategy.
Enhanced feature selection using word embeddings for self-admitted technical debt identification
2 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
A systematic literature review summarizing the shift in SATD detection from heuristic keyword methods to ML, DL, and Transformer models, along with performance trends and open challenges like dataset heterogeneity.
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Quantifying the Impact of Stealthy BLE Spam & Flooding Attacks on IoT Environments
Develops a quantitative foundation for BLE flooding attack impacts on IoT and proposes an agility-based deterrence strategy.
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Self-Admitted Technical Debt Detection Approaches: A Decade Systematic Review
A systematic literature review summarizing the shift in SATD detection from heuristic keyword methods to ML, DL, and Transformer models, along with performance trends and open challenges like dataset heterogeneity.