Moments-Correlating DPA

Moradi, Amir; Standaert, François‐Xavier

doi:10.1145/2996366.2996369

Cited by 52 publications

(40 citation statements)

References 40 publications

(54 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Hamming weight and Hamming distance models are frequently used as a power model. For a leakage model, leakage characterization and average traces are occasionally used, because they are more similar to the actual leakage model than the Hamming weight or Hamming distance . In , an MLP was trained using the Sbox output value and real power trace as the data and label, respectively.…”

Section: Deep Learning‐based Side‐channel Analysismentioning

confidence: 99%

Recent advances in deep learning‐based side‐channel analysis

Jin

Kim

et al. 2020

ETRI Journal

View full text Add to dashboard Cite

As side‐channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side‐channel analysis. However, a drawback of machine learning algorithms is that their performance depends on human engineering. Therefore, recent studies in the field focus on exploiting deep learning algorithms, which can extract features automatically from data. In this study, we survey recent advances in deep learning‐based side‐channel analysis. In particular, we outline how deep learning is applied to side‐channel analysis, based on deep learning architectures and application methods. Furthermore, we describe its properties when using different architectures and application methods. Finally, we discuss our perspective on future research directions in this field.

show abstract

Section: Deep Learning‐based Side‐channel Analysismentioning

confidence: 99%

Recent advances in deep learning‐based side‐channel analysis

Jin

Kim

et al. 2020

ETRI Journal

View full text Add to dashboard Cite

show abstract

“…So we need another ingredient in order to reveal the informativeness of each moment of the leakage PDF, separately. The Moments-Correlating DPA (MC-DPA) recently introduced in [44] is a natural candidate for this purpose. We now describe how it can be used to (informally) analyze the security of a flawed masked implementation.…”

Section: Beyond Independent Leakagementioning

confidence: 99%

Making Masking Security Proofs Concrete

Duc

Faust

Standaert

2015

Advances in Cryptology -- EUROCRYPT 2015

Self Cite

109

View full text Add to dashboard Cite

Abstract. We investigate the relationships between theoretical studies of leaking cryptographic devices and concrete security evaluations with standard side-channel attacks. Our contributions are in four parts. First, we connect the formal analysis of the masking countermeasure proposed by Duc et al. (Eurocrypt 2014) with the Eurocrypt 2009 evaluation framework for side-channel key recovery attacks. In particular, we re-state their main proof for the masking countermeasure based on a mutual information metric, which is frequently used in concrete physical security evaluations. Second, we discuss the tightness of the Eurocrypt 2014 bounds based on experimental case studies. This allows us to conjecture a simplified link between the mutual information metric and the success rate of a side-channel adversary, ignoring technical parameters and proof artifacts. Third, we introduce heuristic (yet well-motivated) tools for the evaluation of the masking countermeasure when its independent leakage assumption is not perfectly fulfilled, as it is frequently encountered in practice. Thanks to these tools, we argue that masking with non-independent leakages may provide improved security levels in certain scenarios. Eventually, we consider the tradeoff between measurement complexity and key enumeration in divide-and-conquer side-channel attacks, and show that it can be predicted based on the mutual information metric, by solving a non-linear integer programming problem for which efficient solutions exist. The combination of these observations enables significant reductions of the evaluation costs for certification bodies.

show abstract

“…In order to relax this requirement moments-correlating DPA (MCDPA) [34] can be applied, that tries to make use of a perfect leakage model by profiling. Therefore, in each core and each chip we divided the collected measurements (n traces) into two halves, and used the first half (n/2 traces) as profiling traces t i∈{1...n/2} .…”

Section: ) Moments-correlating Dpamentioning

confidence: 99%

A Hardware-Based Countermeasure to Reduce Side-Channel Leakage: Design, Implementation, and Evaluation

Gornik

Moradi

Oehm

et al. 2015

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Self Cite

View full text Add to dashboard Cite

Side-channel attacks are one of the major concerns for security-enabled applications as they make use of information leaked by the physical implementation of the underlying cryptographic algorithm. Hence, reducing the side-channel leakage of the circuits realizing the cryptographic primitives is amongst the main goals of circuit designers. In this paper, we present a novel circuit concept, which decouples the main power supply from an internal power supply that is used to drive a single logic gate. The decoupling is done with the help of buffering capacitances integrated into semiconductor. We also introduce-compared to the previously known schemes-an improved decoupling circuit which reduces the crosstalk from the internal to the external power supply. The result of practical side-channel evaluation on a prototype chip fabricated in a 150 nm CMOS technology shows a high potential of our proposed technique to reduce the side-channel leakages.

show abstract

Moments-Correlating DPA

Cited by 52 publications

References 40 publications

Recent advances in deep learning‐based side‐channel analysis

Recent advances in deep learning‐based side‐channel analysis

Making Masking Security Proofs Concrete

A Hardware-Based Countermeasure to Reduce Side-Channel Leakage: Design, Implementation, and Evaluation

Contact Info

Product

Resources

About