Simple power analysis attack against elliptic curve cryptography processor on FPGA implementation

Kadir, Sahbuddin Abdul; Sasongko, Arif; Zulkifli, Muhammad

doi:10.1109/iceei.2011.6021757

Cited by 9 publications

(4 citation statements)

References 4 publications

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“…Corresponding to their classification horizontal attacks are single-trace attacks, for example SPA or HCA attacks. Practical examples of horizontal attacks against asymmetric cryptographic approaches such RSA or ECC are the SPA described in [7], simple electromagnetic analysis (SEMA) attacks e.g. [8], the Big Mac attack [9], the localized EMA attack [10], horizontal collision correlation analysis (HCCA) attacks [11]- [12] , horizontal DPA and DEMA attacks [13], [14].…”

Section: Background: Verical and Horizontal Attacksmentioning

confidence: 99%

Horizontal Attacks Against ECC: From Simulations to ASIC

Kabin

Dyka

Klann

et al. 2020

Lecture Notes in Computer Science

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In this paper we analyse the impact of different compile options on the success rate of side channel analysis attacks. We run horizontal differential side channel attacks against simulated power traces for the same kP design synthesized using two different compile options after synthesis and after layout. As we are interested in the effect on the produced ASIC we also run the same attack against measured power traces after manufacturing the ASIC. We found that the compile_ultra option reduces the success rate significantly from 5 key candidates with a correctness of between 75 and 90 per cent down to 3 key candidates with a maximum success rate of 72 per cent compared to the simple compile option. Also the success rate after layout shows a very high correlation with the one obtained attacking the measured power and electromagnetic traces, i.e. the simulations are a good indicator of the resistance of the ASIC.

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Section: Background: Verical and Horizontal Attacksmentioning

confidence: 99%

Horizontal Attacks Against ECC: From Simulations to ASIC

Kabin

Dyka

Klann

et al. 2020

Lecture Notes in Computer Science

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“…ECC has speed and security advantages over RSA and Diffie-Hellman [18].It is a replacement for problems found in other public key algorithms like discrete log used in DSA and integer factorization in RSA. The security level of 1024 bits key size of RSA can be achieved by 160 bits of ECC [12]. Computationally also it is much faster and thus suitable for devices with limited computation capability like mobile devices [3].…”

Section: Elliptic Curve Cryptographymentioning

confidence: 99%

Implementation of Non-Repudiation Services in Digital Video Generation & Distribution on Android Devices

Gupta¹,

Lavania²,

Agarwal³

et al. 2015

IJEME

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With the onset of Digital age, digital videos have been highly prevalent in every sphere of our lives and have replaced other sources of entertainment, information sharing & social interaction. With the increasing use of Mobile devices, Internet & its application it has been quite evident that digital videos are generated and distributed with ease. Quite often such videos are used as evidence depending on the kind of information they provide. Since the video has been distributed at a large level it becomes very difficult to identify the generator device of the digital video especially if the case is of objectionable video contents etc. This paper aims at proposing a framework which will embed the generator device information in the video & will make sure the user identification information can't be changed during the distribution process using internet or other networking services (i.e. Bluetooth).

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“…One such risk is side‐channel attack. Side‐channel attack refers to the exploitation of side‐channel leakage information, including, power consumption, electromagnetic emanations, cache‐timing, acoustic vibrations, to recover the secret information processed inside edge device 7‐9 . These leakages are obtained from the edge device while it is processing the sensitive information using a secure algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Side-channel attack refers to the exploitation of side-channel leakage information, including, power consumption, electromagnetic emanations, cache-timing, acoustic vibrations, to recover the secret information processed inside edge device. [7][8][9] These leakages are obtained from the edge device while it is processing the sensitive information using a secure algorithm. There exist various secure cryptographic algorithms, however, elliptic curve cryptographic (ECC) based asymmetric algorithms are preferred for authentication and digital security in the resource-constraint environments due to the efficient processing, and small key size.…”

mentioning

confidence: 99%

Edge enhanced deep learning system for IoT edge device security analytics

Mukhtar

Mehrabi

Kong

et al. 2021

Concurrency and Computation

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The processing of locally harvested data at the physically accessible edge devices opens a new avenue of security threats for edge enhanced analytics. Cryptographic algorithms are used to secure the data being processed on the edge device. However, the implementation weakness of the algorithms on the edge devices can lead to side‐channel attack vulnerability, which is exacerbated with the application of machine‐learning techniques. This research proposes a deep learning‐based system integrated at the edge device to identify the side‐channel leakages. To design such a deep learning‐based system, one of the challenges is formulating the suitable attack model for the underlying target algorithm. Based on the previous findings, three machine learning‐based side‐channel attack models are curated and investigated for the edge device security evaluations. As a test case, the standard elliptic‐curve cryptographic algorithm is selected. Moreover, quantitative analysis is provided for the best attack model selection using standard machine‐learning evaluation metrics. A comparative analysis is performed on the raw unaligned data samples and reduced feature‐engineered samples using edge enhanced security analytics. The investigation concludes that the vulnerable algorithm implementation can lead to the secret key recovery from the edge device, with 96% accuracy, using a neural‐network‐based algorithm to analyse side‐channel attacks.

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Simple power analysis attack against elliptic curve cryptography processor on FPGA implementation

Cited by 9 publications

References 4 publications

Horizontal Attacks Against ECC: From Simulations to ASIC

Horizontal Attacks Against ECC: From Simulations to ASIC

Implementation of Non-Repudiation Services in Digital Video Generation & Distribution on Android Devices

Edge enhanced deep learning system for IoT edge device security analytics

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