首页|A Fine-Grained Flash-Memory Fragment Recog-nition Approach for Low-Level Data Recovery

A Fine-Grained Flash-Memory Fragment Recog-nition Approach for Low-Level Data Recovery

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Data recovery from flash memory in the mobile device can effectively reduce the loss caused by data corruption.Type recognition of data fragment is an essential prerequisite to the low-level data recovery.Pre-vious works in this field classify data fragment based on its file type.Still,the classification efficiency is low,espe-cially when the data fragment is a part of a composite file.We propose a fine-grained approach to classifying data fragment from the low-level flash memory to improve the classification accuracy and efficiency.The proposed meth-od redefines flash-memory-page data recognition problem based on the encoding format of the data segment,and applies a hybrid machine learning algorithm to detect the data type of the flash page.The hybrid algorithm can sig-nificantly decompose the given data space and reduce the cost of training.The experimental results show that our method achieves better classification accuracy and higher time performance than the existing methods.

Flash fragmentation recognitionFine-grainedMachine learning algorithmSupport vector ma-chineDecision treeDigital forensics

ZHANG Li、HAO Shengang、ZHANG Quanxin

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Department of Media Engineering,Zhejiang University of Media and Communication,Hangzhou 310018,China

School of Computer Science,Beijing Institute of Technology,Beijing 100081,China

国家自然科学基金

61802210

2022

电子学报(英文)

电子学报(英文)

CSTPCDSCIEI
ISSN:1022-4653
年,卷(期):2022.31(4)
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