Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key de...Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.展开更多
Leakage power analysis(LPA) attacks aim at finding the secret key of a cryptographic device from measurements of its static(leakage) power. This novel power analysis attacks take advantage of the dependence of the lea...Leakage power analysis(LPA) attacks aim at finding the secret key of a cryptographic device from measurements of its static(leakage) power. This novel power analysis attacks take advantage of the dependence of the leakage power of complementary metal oxide semiconductor(CMOS) integrated circuits on the data they process. This paper proposes symmetric dual-rail logic(SDRL), a standard cell LPA attack countermeasure that theoretically resists the LPA attacks. The technique combines standard building blocks to make new compound standard cells, which are close to constant leakage power consumption. Experiment results show SDRL is a promising approach to implement an LPA-resistant crypto processor.展开更多
Side-channel analysis(SCA)has become an increasing important method to assess the physical security of cryptographic systems.In the process of SCA,the number of attack data directly determines the performance of SCA.W...Side-channel analysis(SCA)has become an increasing important method to assess the physical security of cryptographic systems.In the process of SCA,the number of attack data directly determines the performance of SCA.With sufficient attack data,the adversary can achieve a successful SCA.However,in reality,the cryptographic device may be protected with some countermeasures to limit the number of encryptions using the same key.In this case,the adversary cannot use casual numbers of data to perform SCA.The performance of SCA will be severely dropped if the attack traces are insufficient.In this paper,we introduce wavelet scatter transform(WST)and short-time fourier transform(STFT)to non-profiled side-channel analysis domains,to improve the performance of side-channel attacks in the context of insufficient data.We design a practical framework to provide suitable parameters for WST/STFT-based SCA.Using the proposed method,the WST/STFT-based SCA method can significantly enhance the performance and robustness of non-profiled SCA.The practical attacks against four public datasets show that the proposed method is able to achieve more robust performance.Compared with the original correlation power analysis(CPA),the number of attack data can be reduced by 50–95%.展开更多
基金supported by the Hunan Provincial Natrual Science Foundation of China(2022JJ30103)“the 14th Five-Year”Key Disciplines and Application Oriented Special Disciplines of Hunan Province(Xiangjiaotong[2022],351)the Science and Technology Innovation Program of Hunan Province(2016TP1020).
文摘Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.
基金the Software and Integrated CircuitIndustries Development Foundation of Shanghai(No.12Z116010001)
文摘Leakage power analysis(LPA) attacks aim at finding the secret key of a cryptographic device from measurements of its static(leakage) power. This novel power analysis attacks take advantage of the dependence of the leakage power of complementary metal oxide semiconductor(CMOS) integrated circuits on the data they process. This paper proposes symmetric dual-rail logic(SDRL), a standard cell LPA attack countermeasure that theoretically resists the LPA attacks. The technique combines standard building blocks to make new compound standard cells, which are close to constant leakage power consumption. Experiment results show SDRL is a promising approach to implement an LPA-resistant crypto processor.
基金This work is supported in part by National Key R&D Program of China(No.2022YFB3103800)National Natural Science Foundation of China(No.U1936209,No.62002353,No.62202231 and No.62202230)+2 种基金China Postdoctoral Science Foundation(No.2021M701726)Jiangsu Funding Program for Excellent Postdoctoral Talent(No.2022ZB270)Yunnan Provincial Major Science and Technology Special Plan Projects(No.202103AA080015).
文摘Side-channel analysis(SCA)has become an increasing important method to assess the physical security of cryptographic systems.In the process of SCA,the number of attack data directly determines the performance of SCA.With sufficient attack data,the adversary can achieve a successful SCA.However,in reality,the cryptographic device may be protected with some countermeasures to limit the number of encryptions using the same key.In this case,the adversary cannot use casual numbers of data to perform SCA.The performance of SCA will be severely dropped if the attack traces are insufficient.In this paper,we introduce wavelet scatter transform(WST)and short-time fourier transform(STFT)to non-profiled side-channel analysis domains,to improve the performance of side-channel attacks in the context of insufficient data.We design a practical framework to provide suitable parameters for WST/STFT-based SCA.Using the proposed method,the WST/STFT-based SCA method can significantly enhance the performance and robustness of non-profiled SCA.The practical attacks against four public datasets show that the proposed method is able to achieve more robust performance.Compared with the original correlation power analysis(CPA),the number of attack data can be reduced by 50–95%.