On the Optimization of Side-Channel Attacks by Advanced Stochastic Methods

Schindler, Werner

doi:10.1007/978-3-540-30580-4_7

Cited by 22 publications

(21 citation statements)

References 17 publications

(52 reference statements)

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“…The interested reader is referred to [14], Sect. 4 (see also [13], Sect. 7) where such a sieving algorithm was introduced for a timing attack on a weak AES implementation.…”

Section: Suitable Covariance Matrix C) and If Kmentioning

confidence: 95%

“…Using such methods, the efficiency of some known attacks could be increased considerably (up to a factor of fifty), some attacks could be generalized and new attacks were conceived ( [12,13,14]). The understanding of the source of an attack and its true risk potential is important for a designer of a cryptographic system for implementing effective and reliable countermeasures that prevent also privileged attacks.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Stochastic Model for Differential Side Channel Cryptanalysis

Schindler

Lemke²,

Paar³

2005

Lecture Notes in Computer Science

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Abstract. This contribution presents a new approach to optimize the efficiency of differential side channel cryptanalysis against block ciphers by advanced stochastic methods. We approximate the real leakage function within a suitable vector subspace. Under appropriate conditions profiling requires only one test key. For the key extraction we present a 'minimum principle' that solely uses deterministic data dependencies and the 'maximum likelihood principle' that additionally incorporates the characterization of the noise revealed during profiling. The theoretical predictions are accompanied and confirmed by experiments. We demonstrate that the adaptation of probability densities is clearly advantageous regarding the correlation method, especially, if multiple leakage signals at different times can be jointly evaluated. Though our efficiency at key extraction is limited by template attacks profiling is much more efficient which is highly relevant if the designer of a cryptosystem is bounded by the number of measurements in the profiling step.

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“…The interested reader is referred to [14], Sect. 4 (see also [13], Sect. 7) where such a sieving algorithm was introduced for a timing attack on a weak AES implementation.…”

Section: Suitable Covariance Matrix C) and If Kmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

A Stochastic Model for Differential Side Channel Cryptanalysis

Schindler

Lemke²,

Paar³

2005

Lecture Notes in Computer Science

Self Cite

379

280

View full text Add to dashboard Cite

show abstract

“…These attacks were generalized and optimized by advanced stochastic methods (cf. [9,11,12]). In particular, the efficiency of the attack from [5] could be increased by a factor of 50.…”

Section: Introductionmentioning

confidence: 97%

Improving Brumley and Boneh timing attack on unprotected SSL implementations

Acıiçmez

Schindler

Koç

2005

Proceedings of the 12th ACM Conference on Computer and Communications Security

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Since the remarkable work of Kocher [7], several papers considering different types of timing attacks have been published. In 2003, Brumley and Boneh presented a timing attack on unprotected OpenSSL implementations [2]. In this paper, we improve the efficiency of their attack by a factor of more than 10. We exploit the timing behavior of Montgomery multiplications in the table initialization phase, which allows us to increase the number of multiplications that provide useful information to reveal one of the prime factors of RSA moduli. We also present other improvements, which can be applied to the attack in [2].

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“…In the first phase, the adversary analyzes the profiling device in order to approximate the leakage behavior and in the second phase, the adversary attacks the target device. Typical examples are the template-based attack (TA) [5], [6] and Stochastic Approach (SA) [7], [8]. The practical aspects of template attacks (TA) have been discussed in [9], [10].…”

Section: Introductionmentioning

confidence: 99%