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Bibliographic Details
Main Authors:	Ahn, Na Young, Lee, Dong Hoon
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security H.3
Online Access:	https://arxiv.org/abs/2506.02030
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Table of Contents:

Data remanence in NAND flash complicates complete deletion on IoT SSDs. We design an adaptive architecture offering four privacy levels (PL0-PL3) that select among address, data, and parity deletion techniques. Quantitative analysis balances efficacy, latency, endurance, and cost. Machine-learning adjusts levels contextually, boosting privacy with negligible performance overhead and complexity.