Biblio
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On Countermeasures Against the Thermal Covert Channel Attacks Targeting Many-core Systems. 2020 57th ACM/IEEE Design Automation Conference (DAC). :1—6.
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2020. Although it has been demonstrated in multiple studies that serious data leaks could occur to many-core systems thanks to the existence of the thermal covert channels (TCC), little has been done to produce effective countermeasures that are necessary to fight against such TCC attacks. In this paper, we propose a three-step countermeasure to address this critical defense issue. Specifically, the countermeasure includes detection based on signal frequency scanning, positioning affected cores, and blocking based on Dynamic Voltage Frequency Scaling (DVFS) technique. Our experiments have confirmed that on average 98% of the TCC attacks can be detected, and with the proposed defense, the bit error rate of a TCC attack can soar to 92%, literally shutting down the attack in practical terms. The performance penalty caused by the inclusion of the proposed countermeasures is only 3% for an 8×8 system.
A Worst-Case Entropy Estimation of Oscillator-Based Entropy Sources: When the Adversaries Have Access to the History Outputs. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :152—159.
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2019. Entropy sources are designed to provide unpredictable random numbers for cryptographic systems. As an assessment of the sources, Shannon entropy is usually adopted to quantitatively measure the unpredictability of the outputs. In several related works about the entropy evaluation of ring oscillator-based (RO-based) entropy sources, authors evaluated the unpredictability with the average conditional Shannon entropy (ACE) of the source, moreover provided a lower bound of the ACE (LBoACE). However, in this paper, we have demonstrated that when the adversaries have access to the history outputs of the entropy source, for example, by some intrusive attacks, the LBoACE may overestimate the actual unpredictability of the next output for the adversaries. In this situation, we suggest to adopt the specific conditional Shannon entropy (SCE) which exactly measures the unpredictability of the future output with the knowledge of previous output sequences and so is more consistent with the reality than the ACE. In particular, to be conservative, we propose to take the lower bound of the SCE (LBoSCE) as an estimation of the worst-case entropy of the sources. We put forward a detailed method to estimate this worst-case entropy of RO-based entropy sources, which we have also verified by experiment on an FPGA device. We recommend to adopt this method to provide a conservative assessment of the unpredictability when the entropy source works in a vulnerable environment and the adversaries might obtain the previous outputs.
Random Number Generator Based on Hydrogen Gas Sensor for Security Applications. 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS). :709–712.
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2018. Cryptographic applications need high-quality random number generator (RNG) for strong security and privacy measures. This paper presents RNG based on a hydrogen gas sensor that is fabricated by using microfabrication techniques. The proposed approach extracts the thermal noise information as an entropy source from the gas sensor that is non-deterministic during its operation and using hash function SHA-256 as post processing. This non-deterministic noise is then processed to acquire a random number set fulfilling the NIST 800-22 statistical randomness test suite and it demonstrates that a gas sensor based RNG can provide high-quality random numbers. Secure data transfer is possible by having this method directly without any other hardware where hydrogen gas sensor needs to be used such as petrochemical field, fuel cells, and nuclear reactors.