Fault attacks have emerged as an increasingly effective approach for integrated circuit security attacks due to their short execution time and minimal data requirement.However,the lack of a unified leakage model remai...Fault attacks have emerged as an increasingly effective approach for integrated circuit security attacks due to their short execution time and minimal data requirement.However,the lack of a unified leakage model remains a critical challenge,as existing methods often rely on algorithm-specific details or prior knowledge of plaintexts and intermediate values.This paper proposes the Fault Probability Model based on Hamming Weight(FPHW)to address this.This novel statistical framework quantifies fault attacks by solely analyzing the statistical response of the target device,eliminating the need for attack algorithm details or implementation specifics.Building on this model,a Fault Injection Attack method based on Mutual Information(FPMIA)is introduced,which recovers keys by leveraging the mutual information between measured fault probability traces and simulated leakage derived from Hamming weight,reducing data requirements by at least 44%compared to the existing Mutual Information Analysis method while achieving a high correlation coefficient of 0.9403 between measured and modeled fault probabilities.Experimental validation on an AES-128 implementation via a Microcontroller Unit demonstrates that FPHW accurately captures the data dependence of fault probability and FPMIA achieves efficient key recovery with robust noise tolerance,establishing a unified and efficient framework that surpasses traditional methods in terms of generality,data efficiency,and practical applicability.展开更多
As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by havin...As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.展开更多
文摘Fault attacks have emerged as an increasingly effective approach for integrated circuit security attacks due to their short execution time and minimal data requirement.However,the lack of a unified leakage model remains a critical challenge,as existing methods often rely on algorithm-specific details or prior knowledge of plaintexts and intermediate values.This paper proposes the Fault Probability Model based on Hamming Weight(FPHW)to address this.This novel statistical framework quantifies fault attacks by solely analyzing the statistical response of the target device,eliminating the need for attack algorithm details or implementation specifics.Building on this model,a Fault Injection Attack method based on Mutual Information(FPMIA)is introduced,which recovers keys by leveraging the mutual information between measured fault probability traces and simulated leakage derived from Hamming weight,reducing data requirements by at least 44%compared to the existing Mutual Information Analysis method while achieving a high correlation coefficient of 0.9403 between measured and modeled fault probabilities.Experimental validation on an AES-128 implementation via a Microcontroller Unit demonstrates that FPHW accurately captures the data dependence of fault probability and FPMIA achieves efficient key recovery with robust noise tolerance,establishing a unified and efficient framework that surpasses traditional methods in terms of generality,data efficiency,and practical applicability.
基金Iran National Science Foundation,Grant/Award Number:99009224。
文摘As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.
