Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend P...Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend PC oracle based side-channel attacks to the second-order scenario and successfully conduct key-recovery attacks on the first-order masked Kyber.Firstly,we analyze the potential joint information leakage.Inspired by the binary PC oracle based attack proposed by Qin et al.at Asiacrypt 2021,we identify the 1-bit leakage scenario in the masked Keccak implementation.Moreover,we modify the ciphertexts construction described by Tanaka et al.at CHES 2023,extending the leakage scenario from 1-bit to 32-bit.With the assistance of TVLA,we validate these leakages through experiments.Secondly,for these two scenarios,we construct a binary PC oracle based on t-test and a multiple-valued PC oracle based on neural networks.Furthermore,we conduct practical side-channel attacks on masked Kyber by utilizing our oracles,with the implementation running on an ARM Cortex-M4 microcontroller.The demonstrated attacks require a minimum of 15788 and 648 traces to fully recover the key of Kyber768 in the 1-bit leakage scenario and the 32-bit leakage scenario,respectively.Our analysis may also be extended to attack other post-quantum schemes that use the same masked hash function.Finally,we apply the shuffling strategy to the first-order masked imple-mentation of the Kyber and perform leakage tests.Experimental results show that the combination strategy of shuffling and masking can effectively resist our proposed attacks.展开更多
We demonstrate a brand-new method to sharpen a color image by using an integral mask-filtering technique. The derivatives between the target pixel and its neighbors are transferred by the cubic root function instead o...We demonstrate a brand-new method to sharpen a color image by using an integral mask-filtering technique. The derivatives between the target pixel and its neighbors are transferred by the cubic root function instead of the traditional linear one. The obtained final image has clearer fine characteristics along with much less overshooting.展开更多
海洋锋是重要的中尺度海洋现象,具有数据量小、目标小、弱边缘等特性。针对实际检测任务中弱边缘、小目标海洋锋的检测精度低、错检及漏检率高等问题,融合scSE(spatial and channel Squeeze&Excitation)空间注意力模块构建了一种改...海洋锋是重要的中尺度海洋现象,具有数据量小、目标小、弱边缘等特性。针对实际检测任务中弱边缘、小目标海洋锋的检测精度低、错检及漏检率高等问题,融合scSE(spatial and channel Squeeze&Excitation)空间注意力模块构建了一种改进的Mask R-CNN海洋锋检测模型。该方法首先对Mask R-CNN骨干网络结构进行改进,采用scSE模块引导的ResNet-50网络作为特征提取网络,通过加权策略对图像通道和空间位置进行特征突出,提升网络对重要特征的提取能力;其次,针对海洋锋目标边缘定位不准确的问题,引入IoU boundary loss构建新的Mask损失函数,提高边界检测精度。最后,为验证方法的有效性,从训练数据和实验模型上,分别设计多组对比实验。实验结果表明,相比传统Mask R-CNN、YOLOv3神经网络及现有Mask R-CNN改进网络,本文方法对SST梯度影像数据集上的强、弱海洋锋检测效果最好,定位准确率(IoU,Intersection-over-union))及检测精度(mAP,Mean Average Precision)均达0.914以上。此外,对文中设计评估模型进行检测效率实验,结果发现在不同网络模型、不同迭代次数情况下,本文提出模型消耗时间最短,远低于YOLOv3网络完成训练时所用时长。展开更多
针对公共场所口罩佩戴检测存在遮挡、密集和小尺度的情况而导致检测精度不高的问题,以实时目标检测算法YOLOv3为基础提出一种Mask-YOLO算法。首先在特征融合过程中引入通道注意力机制以突出重要特征,减少了融合后冗余特征的影响,有效提...针对公共场所口罩佩戴检测存在遮挡、密集和小尺度的情况而导致检测精度不高的问题,以实时目标检测算法YOLOv3为基础提出一种Mask-YOLO算法。首先在特征融合过程中引入通道注意力机制以突出重要特征,减少了融合后冗余特征的影响,有效提高了特征利用率;然后以完全交并比(complete intersection over union,CIoU)损失代替均方差损失(mean square error,MSE)作为边框回归的损失函数,提高了定位精度;最后除了检测佩戴和未佩戴口罩的情况外,还对不正确佩戴口罩的情况进行了检测。实验结果表明:与YOLOv3算法相比,Mask-YOLO算法在每秒帧率(frame per second,FPS)仅下降1%的情况下使平均精度均值(mean average precision,mAP)提高了4.78%。与其他主流的目标检测算法相比,Mask-YOLO算法在复杂场景下对口罩佩戴检测也有更好的效果和鲁棒性。展开更多
This paper is devoted to investigating the solutions of refinement equations of the form Ф（x）=∑α∈Z^s α（α）Ф（Mx-α）,x∈R^s,where the vector of functions Ф = （Ф1,… ,Фr）^T is in （L1（R^s））^r, α =（...This paper is devoted to investigating the solutions of refinement equations of the form Ф（x）=∑α∈Z^s α（α）Ф（Mx-α）,x∈R^s,where the vector of functions Ф = （Ф1,… ,Фr）^T is in （L1（R^s））^r, α =（α（α））α∈Z^s is an infinitely supported sequence of r × r matrices called the refinement mask, and M is an s × s integer matrix such that lim n→∞ M^-n =0, with m = detM. Some properties about the solutions of refinement equations axe obtained.展开更多
因传统方法单一使用遥感影像或兴趣点(point of interest,POI)数据识别城市功能区时,存在城市特征信息利用不完全、识别精度不高的问题,提出利用POI数据、遥感影像等多源数据,并将自然特征和人文特征相结合,采用基于掩膜区域卷积神经网...因传统方法单一使用遥感影像或兴趣点(point of interest,POI)数据识别城市功能区时,存在城市特征信息利用不完全、识别精度不高的问题,提出利用POI数据、遥感影像等多源数据,并将自然特征和人文特征相结合,采用基于掩膜区域卷积神经网络和样方密度法(mask region based convolutional neural network and quadrat density method,Mask R-CNN-QDM)模型识别城市功能区的方法。首先基于遥感影像采用Mask R-CNN模型识别建筑物,然后将识别结果与POI数据进行补充校验,得到结合自然特征和人文特征的分类结果,再引入面积要素对分类结果进行赋分,以计算样方密度,并采用随机抽样方式对所提方法功能区的识别精度进行评价。研究结果表明,Mask R-CNN-QDM模型的识别精确度高达0.900,平均Kappa系数为0.802,说明该方法能较好地区分单一城市功能区和混合城市功能区。展开更多
The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are ...The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are vulnerable to malicious attacks.Although numerous researchers have proposed authentication schemes to enhance the security of Vehicle-to-Vehicle(V2V)communication,most existing methodologies face two significant challenges:(1)the majority of the schemes are not lightweight enough to support realtime message interaction among vehicles;(2)the sensitive information like identity and position is at risk of being compromised.To tackle these issues,we propose a lightweight dual authentication protocol for V2V communication based on Physical Unclonable Function(PUF).The proposed scheme accomplishes dual authentication between vehicles by the combination of Zero-Knowledge Proof(ZKP)and MASK function.The security analysis proves that our scheme provides both anonymous authentication and information unlinkability.Additionally,the performance analysis demonstrates that the computation overhead of our scheme is approximately reduced 23.4% compared to the state-of-the-art schemes.The practical simulation conducted in a 6G network environment demonstrates the feasibility of 6G-based VANETs and their potential for future advancements.展开更多
在低光环境下,人脸图像增强是许多任务的重要恢复方法。然而,现有的低光环境下人脸超分辨率方法通常依赖于低光增强和超分算法的序列建模。遗憾的是,由于优化目标之间的差异,使用这种方法来增强人脸图像很容易导致伪影或噪声。为了应对...在低光环境下,人脸图像增强是许多任务的重要恢复方法。然而,现有的低光环境下人脸超分辨率方法通常依赖于低光增强和超分算法的序列建模。遗憾的是,由于优化目标之间的差异,使用这种方法来增强人脸图像很容易导致伪影或噪声。为了应对这一挑战,本文提出了一个端到端的低光人脸图像超分辨率网络(low-light face super resolution network,LFSRNet)。该网络由浅层特征提取、深层特征提取和特征过滤上采样3个模块组成。首先浅层特征模块将输入的低光、低分辨率人脸图像映射到特征空间。随后,深度特征提取模块对其进行亮度校正并细化结构。最后,特征过滤上采样模块处理提取到的特征并重建人脸图像。此外,为了更好地重建丢失的面部细节本文还设计了一个损失函数faceMaskLoss。大量实验证明了所提模型的有效性。展开更多
基金National Natural Science Foundation of China(62472397)Innovation Program for Quantum Science and Technology(2021ZD0302902)。
文摘Recently,several PC oracle based side-channel attacks have been proposed against Kyber.However,most of them focus on unprotected implementations and masking is considered as a counter-measure.In this study,we extend PC oracle based side-channel attacks to the second-order scenario and successfully conduct key-recovery attacks on the first-order masked Kyber.Firstly,we analyze the potential joint information leakage.Inspired by the binary PC oracle based attack proposed by Qin et al.at Asiacrypt 2021,we identify the 1-bit leakage scenario in the masked Keccak implementation.Moreover,we modify the ciphertexts construction described by Tanaka et al.at CHES 2023,extending the leakage scenario from 1-bit to 32-bit.With the assistance of TVLA,we validate these leakages through experiments.Secondly,for these two scenarios,we construct a binary PC oracle based on t-test and a multiple-valued PC oracle based on neural networks.Furthermore,we conduct practical side-channel attacks on masked Kyber by utilizing our oracles,with the implementation running on an ARM Cortex-M4 microcontroller.The demonstrated attacks require a minimum of 15788 and 648 traces to fully recover the key of Kyber768 in the 1-bit leakage scenario and the 32-bit leakage scenario,respectively.Our analysis may also be extended to attack other post-quantum schemes that use the same masked hash function.Finally,we apply the shuffling strategy to the first-order masked imple-mentation of the Kyber and perform leakage tests.Experimental results show that the combination strategy of shuffling and masking can effectively resist our proposed attacks.
文摘We demonstrate a brand-new method to sharpen a color image by using an integral mask-filtering technique. The derivatives between the target pixel and its neighbors are transferred by the cubic root function instead of the traditional linear one. The obtained final image has clearer fine characteristics along with much less overshooting.
文摘针对公共场所口罩佩戴检测存在遮挡、密集和小尺度的情况而导致检测精度不高的问题,以实时目标检测算法YOLOv3为基础提出一种Mask-YOLO算法。首先在特征融合过程中引入通道注意力机制以突出重要特征,减少了融合后冗余特征的影响,有效提高了特征利用率;然后以完全交并比(complete intersection over union,CIoU)损失代替均方差损失(mean square error,MSE)作为边框回归的损失函数,提高了定位精度;最后除了检测佩戴和未佩戴口罩的情况外,还对不正确佩戴口罩的情况进行了检测。实验结果表明:与YOLOv3算法相比,Mask-YOLO算法在每秒帧率(frame per second,FPS)仅下降1%的情况下使平均精度均值(mean average precision,mAP)提高了4.78%。与其他主流的目标检测算法相比,Mask-YOLO算法在复杂场景下对口罩佩戴检测也有更好的效果和鲁棒性。
基金Supported by the National Natural Science Foundation of China (10071071)
文摘This paper is devoted to investigating the solutions of refinement equations of the form Ф（x）=∑α∈Z^s α（α）Ф（Mx-α）,x∈R^s,where the vector of functions Ф = （Ф1,… ,Фr）^T is in （L1（R^s））^r, α =（α（α））α∈Z^s is an infinitely supported sequence of r × r matrices called the refinement mask, and M is an s × s integer matrix such that lim n→∞ M^-n =0, with m = detM. Some properties about the solutions of refinement equations axe obtained.
文摘因传统方法单一使用遥感影像或兴趣点(point of interest,POI)数据识别城市功能区时,存在城市特征信息利用不完全、识别精度不高的问题,提出利用POI数据、遥感影像等多源数据,并将自然特征和人文特征相结合,采用基于掩膜区域卷积神经网络和样方密度法(mask region based convolutional neural network and quadrat density method,Mask R-CNN-QDM)模型识别城市功能区的方法。首先基于遥感影像采用Mask R-CNN模型识别建筑物,然后将识别结果与POI数据进行补充校验,得到结合自然特征和人文特征的分类结果,再引入面积要素对分类结果进行赋分,以计算样方密度,并采用随机抽样方式对所提方法功能区的识别精度进行评价。研究结果表明,Mask R-CNN-QDM模型的识别精确度高达0.900,平均Kappa系数为0.802,说明该方法能较好地区分单一城市功能区和混合城市功能区。
文摘The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are vulnerable to malicious attacks.Although numerous researchers have proposed authentication schemes to enhance the security of Vehicle-to-Vehicle(V2V)communication,most existing methodologies face two significant challenges:(1)the majority of the schemes are not lightweight enough to support realtime message interaction among vehicles;(2)the sensitive information like identity and position is at risk of being compromised.To tackle these issues,we propose a lightweight dual authentication protocol for V2V communication based on Physical Unclonable Function(PUF).The proposed scheme accomplishes dual authentication between vehicles by the combination of Zero-Knowledge Proof(ZKP)and MASK function.The security analysis proves that our scheme provides both anonymous authentication and information unlinkability.Additionally,the performance analysis demonstrates that the computation overhead of our scheme is approximately reduced 23.4% compared to the state-of-the-art schemes.The practical simulation conducted in a 6G network environment demonstrates the feasibility of 6G-based VANETs and their potential for future advancements.
文摘在低光环境下,人脸图像增强是许多任务的重要恢复方法。然而,现有的低光环境下人脸超分辨率方法通常依赖于低光增强和超分算法的序列建模。遗憾的是,由于优化目标之间的差异,使用这种方法来增强人脸图像很容易导致伪影或噪声。为了应对这一挑战,本文提出了一个端到端的低光人脸图像超分辨率网络(low-light face super resolution network,LFSRNet)。该网络由浅层特征提取、深层特征提取和特征过滤上采样3个模块组成。首先浅层特征模块将输入的低光、低分辨率人脸图像映射到特征空间。随后,深度特征提取模块对其进行亮度校正并细化结构。最后,特征过滤上采样模块处理提取到的特征并重建人脸图像。此外,为了更好地重建丢失的面部细节本文还设计了一个损失函数faceMaskLoss。大量实验证明了所提模型的有效性。
