A Comprehensive Survey on the Non-Invasive Passive Side-Channel Analysis

Socha, Petr; Miškovský, Vojtěch; Novotný, Martin

doi:10.3390/s22218096

Cited by 6 publications

(4 citation statements)

References 130 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent studies emphasize the importance of mitigating these attacks through various countermeasures. In [40], Socha et al provided a comprehensive overview of the impact of side-channel attacks on both hardware and software cryptographic implementations. Additionally, Vanhoef et al [41] presented a timing attack against an encoding method to elliptic curve points, exploiting timing leaks generated by arithmetic operations behind ECC.…”

Section: Side-channel Attacksmentioning

confidence: 99%

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Lahraoui,

Lazaar,

Amal

et al. 2024

Cryptography

View full text Add to dashboard Cite

To ensure the security of sensitive data, elliptic curve cryptography (ECC) is adopted as an asymmetric method that balances security and efficiency. Nevertheless, embedding messages into elliptic curve (EC) points poses a significant challenge. The intricacies of this process can greatly affect the overall security and efficiency of the cryptosystem, reflecting security vulnerabilities observed in many existing schemes that utilize ElGamal ECC-based encryption. In this paper, we introduce an innovative hash-based technique for securely embedding messages into EC points before encryption. A random parameter and a shared secret point generated through the EC Diffie–Hellman protocol are used to bolster the scheme’s security. The security of the proposed method is evaluated against various attack models; moreover, the complexity, and sensitivity of the encryption scheme, as well as its inputs, are analyzed. The randomness assessment of the ciphertext was performed using the NIST statistical test suite. Additionally, we propose a mechanism to ensure the integrity of the message by securely appending a tag to the ciphertext. As a consequence, a comprehensive analysis of our scheme demonstrates its effectiveness in maintaining data security and integrity against various attack models. The algorithm also meets more criteria such as the strict avalanche criterion, linear complexity, and operability.

show abstract

Section: Side-channel Attacksmentioning

confidence: 99%

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Lahraoui,

Lazaar,

Amal

et al. 2024

Cryptography

View full text Add to dashboard Cite

show abstract

“…Here, r out and r [3] are the output mask of the recomputedsbox and linear mask of the AES state, respectively. We show the SNR calculated from the raw traces and the CWT coefficients for the previous four values in Figure 1 (jitter-free) and Figure 2 (jittery).…”

Section: Advantages Of Wavelet Transform In Side-channel Analysismentioning

confidence: 99%

“…Therefore, hardware (implementation) level security of a cryptographic algorithm cannot be guaranteed, even if the algorithm or scheme level security has been mathematically proven unless side-channel analysis-specific countermeasures are investigated. For this reason, side-channel analysis is still actively researched in cryptanalysis/hardware security academia and the semiconductor industry [3].…”

Section: Introductionmentioning

confidence: 99%

Autoscaled-Wavelet Convolutional Layer for Deep Learning-Based Side-Channel Analysis

Bae,

Park,

Kim

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Continuous Wavelet Transform (CWT) is rarely used in the field of side-channel analysis due to problems related to parameter (wavelet scale) selection; There is no way to find the optimal wavelet scale other than an exhaustive search, and the resulting spectrogram analysis can introduce significant analysis complexity. However, a well-scaled CWT can improve the signal-to-noise ratio of side-channel signals, which can lead to better attack performance. And our insights suggest that there is scope for CWT and deep learning approaches to be combined, which could help the models to train more effectively while overcoming the problems of CWT. In this context, we propose a novel feature extraction layer that combines a CWT with a Convolutional Neural Network (CNN). The proposed method can leverage neural network training to automatically adjust a wavelet scale, which is a critical parameter of CWT. Furthermore, the proposed method can lead to performance improvements by enabling a deep learning model to perform onthe-fly multi-frequency analysis without any pre-processing. By bringing the two approaches together, we were able to overcome the limitations of CWT and improve the performance of deep learning-based sidechannel analysis. As an experimental result using open dataset ASCAD, a de facto standard in deep learningbased side-channel analysis, we confirmed that the proposed method could improve the performance by inserting the proposed layer into existing state-of-the-art deep learning models.

show abstract

“…To obtain the secret key, this paper proposes a variety of power analysis attacks that make use of either profiling or nonprofiling techniques that are based on Convolutional Neural Network (CNN) [11] models. Since Z originally presented the concept of side-channel attack, there have been several fascinating advancements in the actual research that has been conducted in this sector [12].…”

Section: Introductionmentioning

confidence: 99%

Design of Deep Learning Techniques for Side-Channel Attacks on Masked 128-bit AES Implementations

Saeb Nahi,

Fattah,

Mutashar

et al. 2024

KJCS

View full text Add to dashboard Cite

Researchers are exploring the use of convolutional neural networks (CNNs) in side-channel attacks to understand the weaknesses in cryptographic implementation. CNNs can learn hierarchical characteristics automatically from electromagnetic radiation or power usage during cryptographic processes. Researchers train CNNs on side-channel data to extract meaningful representations and deduce secret keys. Deep learning algorithms are helpful in evaluating the security of embedded systems, and CNNs are a feasible paradigm for profiling side-channel analysis attacks. In this paper, it has been introduced a VGG (Visual Geometry Group)-Net architecture, which is a typical deep convolutional neural network design with numerous layers. It uses the ASCAD dataset to conduct experiments. They found that VGG-Net architecture Side Channel Attacks (SCA) provides better results than the previously optimized CNN model by significantly reducing the number of side-channel traces required for successful attacks on desynchronized datasets. The researchers also discovered that synchronous traces serve as the pre-training source for VGG-Net architecture, functioning successfully in terms of jittering with minimal fine-adjusting after training

show abstract

A Comprehensive Survey on the Non-Invasive Passive Side-Channel Analysis

Cited by 6 publications

References 130 publications

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

Autoscaled-Wavelet Convolutional Layer for Deep Learning-Based Side-Channel Analysis

Design of Deep Learning Techniques for Side-Channel Attacks on Masked 128-bit AES Implementations

Contact Info

Product

Resources

About