An Adaptive Memory-Side Encryption Method for Improving Security and Lifetime of PCM-Based Main Memory
In this article, we present a main memory system for improving the lifetime and security of phase-change main memories. Storing encrypted data increases the bit-flip rates in memory cells, which adversely affects the lifetime of the phase-change memory cells. Thus, to improve the lifetime and securi...
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Veröffentlicht in: | IEEE transactions on computer-aided design of integrated circuits and systems 2022-06, Vol.41 (6), p.1744-1756 |
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Zusammenfassung: | In this article, we present a main memory system for improving the lifetime and security of phase-change main memories. Storing encrypted data increases the bit-flip rates in memory cells, which adversely affects the lifetime of the phase-change memory cells. Thus, to improve the lifetime and security, the proposed system reduces the bit-flip rates by introducing two techniques. The first technique is a memory-side encryption which provides security against DIMM stealing attacks. To prevent unauthorized accesses, in this technique, the encrypted data are not saved in the main memory. As the second technique, we suggest an adaptive partial encryption approach, which makes use of behavior tracking of the application in the CPU side to minimize the latency overhead of the first technique. Additionally, it prevents the loss of data against application-based attacks. This technique uses a recurrent neural network (RNN) to do sequence classification and detect malicious applications. In addition, an auxiliary method, called periodic encryption (PE), which overcomes the security loss in some applications induced by the low accuracy of the employed neural network, is presented. The efficacy of the proposed method is evaluated using gem5 simulator and some benchmarks. Compared to DEUCE and Crypto-Comp methods, the results for the lifetime evaluation show an average bit-flip rate reduction of 11%. In addition, the security improvements against the DIMM stealing and application-based attacks are about 100% and 92.5%, respectively. |
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ISSN: | 0278-0070 1937-4151 |
DOI: | 10.1109/TCAD.2021.3093832 |