R&D: ADS Leveraging Approximate Data for Efficient Data Sanitization in SSDs
Experimental results show that ADS reduces the average secure deletion latency by 58.93% over the state-of-the-art.
This is a Press Release edited by StorageNewsletter.com on October 13, 2021 at 1:31 pmIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems has published an article written by Jinhua Cui, Weiguang Liu, School of Computer Science and Technology, Huazhong University of Science and Technology, Hu Bei, 430074, China, Jianhang Huang, School of Electronic and Information Engineering, Xi’an Jiaotong University, Shaanxi, 710049, China, and Laurence T. Yang, School of Computer Science and Technology, Huazhong University of Science and Technology, Hu Bei, 430074, China, and with the Department of Computer Science, St. Francis Xavier University, Antigonish, NS B2G 2W5, Canada.
Abstract: “NAND flash memory has been widely adopted in emerging storage systems. To ensure data security, the support of data sanitization in NAND flash memory-based storage systems is widely employed. Although some existing studies made efforts in employing encryption-based, erasure-based and scrubbing-based secure deletion approaches to achieve the security requirement, they suffer from the risk of being deciphered, the severe performance, and the scrubbing disturbance problems. Meanwhile, 3D NAND flash technology which stacks flash cells in vertical direction is gaining traction in the modern systems. This made the problems more severe because of the increased number of scrubbing disturbance directions in 3D NAND flash memory. To address the above issue, this work proposes ADS, an approximate-data-aware data sanitization scheme with the assistance of the error-resilient data of modern applications, which guarantees the highest degree of security for security-sensitive data sanitization (i.e., storage systems do not keep any old version of secure data once secure data are updated). ADS classifies request data into approx-secure, precise-secure, approx-unsecure, and precise-unsecure data by considering two factors including data error resilience and data privacy. Then, a novel data allocation strategy is proposed to selectively interleave secure data and approximate data within the flash blocks, which creates the scrubbing-friendly data patterns to minimize the overhead of secure deletion. Our experimental results show that, ADS reduces the average secure deletion latency by 58.93% over the state-of-the-art.“
Subscribe to our free daily newsletter
