Information leakage from robust codes protecting cryptographic primitives

2020 ◽  
pp. 301-322
Keyword(s):  
Information Leakage ◽  
Cryptographic Primitives ◽  
Robust Codes

scholarly journals A comment on information leakage from robust code-based checkers detecting fault attacks on cryptographic primitives

10.29007/r2sc ◽  
2019 ◽  
Author(s):  
Osnat Keren ◽  
Ilia Polian
Keyword(s):  
Error Detection ◽  
Fault Injection ◽  
Information Leakage ◽  
Secret Key ◽  
Cryptographic Primitives ◽  
Significant Information ◽  
Injection Attacks ◽  
Robust Codes ◽  
Fault Injection Attacks ◽  
The Relationship

Cryptographic hardware primitives must be protected against fault-injection attacks. Security-oriented error-detecting codes provide (probabilistic) guarantees for detection of maliciously injected faults even under assumption of a sophisticated attacker with access to powerful equipment.In this paper, we revisit the earlier finding that error-detection infrastructure may increase the undesired information leakage. We formalize the information leakage from the checker response by means of mutual information. We apply our analysis to the best security-oriented robust codes known today. We prove that the probability of an undetected attack is exponentially smaller than the entropy loss due to information leak from the checker. This means that an attack will be detected far before the attacker will gain significant information. Given a bound for acceptable information leakage (e.g., 0.5 bits of a 128-bit secret key), our analysis allows the designer to easily choose the number of redundant bits required to stay below that bound. The obtained results extend our knowledge about the relationship between detection capabilities of codes and information leakage due to them.

scholarly journals Illuminating the Dark or how to recover what should not be seen in FE-based classifiers

2020 ◽  
Vol 2020 (2) ◽  
pp. 5-23
Author(s):  
Sergiu Carpov ◽  
Caroline Fontaine ◽  
Damien Ligier ◽  
Renaud Sirdey
Keyword(s):  
Data Privacy ◽  
Information Leakage ◽  
Use Cases ◽  
Security And Privacy ◽  
Functional Encryption ◽  
Cryptographic Primitives ◽  
Encrypted Data ◽  
Current State ◽  
Encryption Schemes ◽  
Privacy Issues

AbstractClassification algorithms/tools become more and more powerful and pervasive. Yet, for some use cases, it is necessary to be able to protect data privacy while benefiting from the functionalities they provide. Among the tools that may be used to ensure such privacy, we are focusing in this paper on functional encryption. These relatively new cryptographic primitives enable the evaluation of functions over encrypted inputs, outputting cleartext results. Theoretically, this property makes them well-suited to process classification over encrypted data in a privacy by design’ rationale, enabling to perform the classification algorithm over encrypted inputs (i.e. without knowing the inputs) while only getting the input classes as a result in the clear.In this paper, we study the security and privacy issues of classifiers using today practical functional encryption schemes. We provide an analysis of the information leakage about the input data that are processed in the encrypted domain with state-of-the-art functional encryption schemes. This study, based on experiments ran on MNIST and Census Income datasets, shows that neural networks are able to partially recover information that should have been kept secret. Hence, great care should be taken when using the currently available functional encryption schemes to build privacy-preserving classification services. It should be emphasized that this work does not attack the cryptographic security of functional encryption schemes, it rather warns the community against the fact that they should be used with caution for some use cases and that the current state-ofthe-art may lead to some operational weaknesses that could be mitigated in the future once more powerful functional encryption schemes are available.

Evaluation of Information Leakage from Cryptographic Hardware via Common-Mode Current

2012 ◽  
Vol E95.C (6) ◽  
pp. 1089-1097 ◽  
Author(s):  
Yu-ichi HAYASHI ◽  
Naofumi HOMMA ◽  
Takaaki MIZUKI ◽  
Takeshi SUGAWARA ◽  
Yoshiki KAYANO ◽  
...  
Keyword(s):  
Information Leakage ◽  
Common Mode ◽  
Cryptographic Hardware

scholarly journals Remote whispering metamaterial for non-radiative transceiving of ultra-weak sound

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jin Zhang ◽  
Wei Rui ◽  
Chengrong Ma ◽  
Ying Cheng ◽  
Xiaojun Liu ◽  
...  
Keyword(s):  
Energy Transfer ◽  
Detection Limit ◽  
Free Space ◽  
Signal To Noise Ratio ◽  
Resonance Energy Transfer ◽  
Information Leakage ◽  
Resonance Energy ◽  
Acoustic Analogy ◽  
Signal To Noise ◽  
Airborne Sound

AbstractTransceiving ultra-weak sound typically relies on signal pre-amplification at the transmitting end via active electro-acoustic devices, which inherently perturbs the environment in the form of noise that inevitably leads to information leakage. Here we demonstrate a passive remote-whispering metamaterial (RWM) enabling weak airborne sound at audible frequencies to reach unprecedented signal enhancement without altering the detected ambient soundscape, which is based on the extraordinary scattering properties of a metamaterial formed by a pair of self-resonating subwavelength Mie meta-cavities, constituting the acoustic analogy of Förster resonance energy transfer. We demonstrate efficient non-radiative sound transfer over distances hundreds times longer than the radius of the meta-cavities, which enables the RWM to recover weak sound signals completely overwhelmed by strong noise with enhanced signal-to-noise ratio from −3 dB below the detection limit of 0 dB in free space to 17.7 dB.

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