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| Content Provider | ACM Digital Library |
|---|---|
| Author | Tu, Chenyang Zhao, Yuan Gao, Neng Zhou, Jian Ma, Yuan Liu, Zeyi |
| Abstract | Low-entropy masking schemes and shuffling technique are two common countermeasures against traditional side-channel analysis. Improved Rotating S-box Masking (RSM) is a combination of both countermeasures and is implemented by DPA contest committee to improve the software security level of AES-128. Compared with the original version, improved RSM mainly introduces both the offset and shuffle array as security foundations to counteract the existing attacks. In this paper, we first point out a general vulnerability referred to as "leakage fingerprints" and make use of it to successfully crack the offset array with 100% accuracy, which breaks down the masking countermeasure in the first step. Then, we show that cracking the shuffle array is still feasible but not necessary since several other vulnerabilities in the implementation level can be exploited to bypass the shuffle countermeasure directly. By selectively combining all these vulnerabilities, a dozen of attacks can be put forward, and we perform two of them as examples to verify their effectiveness. Official evaluation results show that, both attacks submitted by us are practical and feasible, and also operate with high efficiency. In terms of two major performance metrics, our best scheme requires 4 traces to reveal the AES master key with 80% Global Success Rate (GSR) and only 2 traces are enough to reduce the Maximum Partial Guessing Entropy (PGE) under 10. |
| Starting Page | 807 |
| Ending Page | 818 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450342339 |
| DOI | 10.1145/2897845.2897868 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-05-30 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Side-channel analysis Euclidean distance Shuffling Dpa contest v4.2 Leakage fingerprints Low entropy masking schemes |
| Content Type | Text |
| Resource Type | Article |
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