Improved C-Language Implementation of AES Algorithm for WSN

Scripcariu, Luminița; Birladeanu, Andreea-Elena; Mătăsaru, Petre-Daniel

doi:10.1109/isscs52333.2021.9497394

Cited by 2 publications

(2 citation statements)

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“…Researchers implemented AES using different tools, Ramya et al proposed an efficient AES using VLSI [7]. In wireless sensor networks (WSN), Luminiţa et al designed an improved C Language implementation of AES [8]. However, as technology has developed, numerous academics have examined AES's security.…”

Section: Introductionmentioning

confidence: 99%

“…A Dcor fault model that has been developed calls for fewer PCFCs than the existing model. Using the M1 model, for instance, [22] shows that although breaking AES-192 requires two PCFCs and 2 8 exhaustive searches, cracking AES-256 requires three PCFCs and 2 32 exhaustive searches. The proposed Dcor fault model, on the other hand, requires fewer PCFCs and thorough searches to recover AES-192.…”

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confidence: 99%

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A Novel DFA on AES: Based on Two–Byte Fault Model with Discontiguous Rows

et al. 2023

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Differential fault attack (DFA) is a distinctive methodology for acquiring the key to block ciphers, which comprises two distinct strategies: DFA on the state and DFA on the key schedule. Given the widespread adoption of the Advanced Encryption Standard (AES), it has emerged as a prominent target for DFA. This paper presents an efficient DFA on the AES, utilizing a two−byte fault model that induces faults at the state with discontiguous rows. The experiment demonstrates that, based on the proposed fault model, the key for AES–128, AES–192, and AES–256 can be successfully recovered by exploiting two, two, and four faults, respectively, without the need for exhaustive research. Notably, in the case of AES–256, when considering exhaustive research, two (or three) faults are needed with 232 (or 216) exhaustive searches. In comparison to the currently available DFA on the AES state, the proposed attack method shows a higher efficiency due to the reduced induced faults.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%