Hash-based Digital Signature Schemes

Buchmann, Johannes; Dahmen, Erik; Szydlo, Michael

doi:10.1007/978-3-540-88702-7_3

Cited by 49 publications

(47 citation statements)

References 21 publications

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“…It was introduced in [18] and a detailed description of MSS can be found in [7]. Details about the implementation inspiring our work are given in [19].…”

Section: Hash-based Signaturesmentioning

confidence: 99%

“…Hence, algorithms for efficient on-the-fly authentication path computation during signature generation are required. The currently best known algorithm for on-the-fly computation of authentication nodes is the BDS algorithm [7] (Algo. 3, cf.…”

Section: Authentication Path Computationmentioning

confidence: 99%

“…The security properties of the signature scheme described above is discussed in [7]. Specifically, the work shows that the Lamport-Diffie one-time signatures [14] are existentially unforgeable under an adaptive chosen message attack (i.e., CMA-secure), if the chosen one-way function is preimage resistant.…”

Section: Security Of Mssmentioning

confidence: 99%

“…3 can be calculated by counting all invocations of Leafcalc, a function that on input s outputs leaf ν 0 [s]. As mentioned in [7] it is possible to omit Leafcalc in Step 3 of Algo. 3 since the sth W-OTS key pair is used to sign the current message, hence the verification key can be computed from the signature and one additional hash computation yields leaf ν 0 [s].…”

Section: Authentication Path Computationmentioning

confidence: 99%

“…From Treehash 1 we store node ν 0 [7], from Treehash 2 we store nodes ν 1 [7] and ν 0 [15] and so on. More generally, we store h nodes ν j …”

Section: Balanced Authentication Path Computationmentioning

confidence: 99%

See 4 more Smart Citations

A Performance Boost for Hash-Based Signatures

Eisenbarth

Maurich

Paar

et al. 2013

Lecture Notes in Computer Science

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Abstract. Digital signatures have become a key component of many embedded system solutions and are facing strong security and efficiency requirements. In this work, algorithmic improvements for the authentication path computation decrease the average signature computation time by close to 50 % when compared to state-of-the-art algorithms. The proposed scheme is implemented on an Intel Core i7 CPU and an AVR ATxmega microcontroller with optimized versions for the respective target platform. The theoretical algorithmic improvements are verified and cryptographic hardware accelerators are used to achieve competitive performance.

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“…It was introduced in [18] and a detailed description of MSS can be found in [7]. Details about the implementation inspiring our work are given in [19].…”

Section: Hash-based Signaturesmentioning

confidence: 99%

Section: Authentication Path Computationmentioning

confidence: 99%

Section: Security Of Mssmentioning

confidence: 99%

Section: Authentication Path Computationmentioning

confidence: 99%

“…From Treehash 1 we store node ν 0 [7], from Treehash 2 we store nodes ν 1 [7] and ν 0 [15] and so on. More generally, we store h nodes ν j …”

Section: Balanced Authentication Path Computationmentioning

confidence: 99%

See 3 more Smart Citations

A Performance Boost for Hash-Based Signatures

Eisenbarth

Maurich

Paar

et al. 2013

Lecture Notes in Computer Science

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Internet of Things device authentication via electromagnetic fingerprints

Souza

Carlson

Ramos

et al. 2020

Engineering Reports

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We quickly approach a future where Internet of Things (IoT) devices are the norm. In this scenario, humans are surrounded by a multitude of heterogeneous devices that assist them in almost every aspect of their daily routines. The realization of this future demands strong authentication guarantees to ensure that these devices are not abused and that their users are not endangered. However, providing authentication for these systems is challenging due to the high heterogeneity of IoT applications. In this paper, we first review several IoT application scenarios and promising authentication methods for each. We identify th e key characteristics of each IoT application scenario, present the strengths and weaknesses of prominent authentication methods from the literature, and review which authentication methods have been proposed in the literature for each application. Then, we present a novel authentication method for IoT based on electromagnetic noise. The key advantage of electromagnetic noise is that any electronic device intrinsically generates electromagnetic noise during normal operation. We extract features from these electromagnetic emanations and use machine learning algorithms to identify devices based on these features. Our method achieves 77% accuracy when identifying devices among a set of seven devices.

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Chaotic neural networks and farfalle construction based parallel keyed secure hash function

Belal

Maitra

Giri

et al. 2022

Security and Privacy

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Parallel computing of hash functions along with the security requirements have great advantage in order to reduce the time consumption and overhead of the CPU. In this article, a keyed hash function based on farfalle construction and chaotic neural networks (CNNs) is proposed, which generates a hash value with arbitrary (defined by user) length (eg, 256 and 512 bits). The proposed hash function has parallelism merit because it is built over farfalle construction which avoids the dependency between the blocks of a given message. Moreover, the proposed hash function is chaos based (ie, it relies on chaotic maps and CNNs which have non‐periodic behavior). The security analysis shows that the proposed hash function is robust and satisfies the properties of hash algorithms, such as random‐like (non‐periodic) behavior, ideal sensitivity to original message and secret key, one‐way property and optimal diffusion effect. The speed performance of the hash function is also analyzed and compared with a hash function which was built based on sponge construction and CNN, and compared with secure hash algorithm (SHA) variants like SHA‐2 and SHA‐3. The results have shown that the proposed hash function has lower time complexity and higher throughput especially with large size messages. Additionally, the proposed hash function has enough resistance to multiple attacks, such as collision attack, birthday attack, exhaustive key search attack, preimage and second preimage attacks, and meet‐in‐the‐middle attack. These advantages make it ideal to be used as a good collision‐resistant hash function.

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Hash-based Digital Signature Schemes

Cited by 49 publications

References 21 publications

A Performance Boost for Hash-Based Signatures

A Performance Boost for Hash-Based Signatures

Internet of Things device authentication via electromagnetic fingerprints

Chaotic neural networks and farfalle construction based parallel keyed secure hash function

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