The principle of ptychography is applied in known plain text attack on the double random phase encoding （DRPE） system. We find that with several pairs of plain texts and cipher texts, the model of attack on DRPE can...The principle of ptychography is applied in known plain text attack on the double random phase encoding （DRPE） system. We find that with several pairs of plain texts and cipher texts, the model of attack on DRPE can be converted to the model of ptyehographical imaging. Owing to the inherent merits of the ptyehographical imaging, the DRPE system can be breached totally in a fast and nearly perfect way, which is unavailable for currently existing attack methods. Further, since the decryption keys can be seen as an object to be imaged from the perspective of imaging, the ptychographical technique may be a kind of new direction to further analysis of the security of other encryption systems based on double random keys.展开更多
针对网联车队列系统易受到干扰和拒绝服务(Denial of service, DoS)攻击问题,提出一种外部干扰和随机DoS攻击作用下的网联车安全H∞队列控制方法.首先,采用马尔科夫随机过程,将网联车随机DoS攻击特性建模为一个随机通信拓扑切换模型,据...针对网联车队列系统易受到干扰和拒绝服务(Denial of service, DoS)攻击问题,提出一种外部干扰和随机DoS攻击作用下的网联车安全H∞队列控制方法.首先,采用马尔科夫随机过程,将网联车随机DoS攻击特性建模为一个随机通信拓扑切换模型,据此设计网联车安全队列控制协议.然后,采用线性矩阵不等式(Linear matrix inequality, LMI)技术计算安全队列控制器参数,并应用Lyapunov-Krasovskii稳定性理论,建立在外部扰动和随机DoS攻击下队列系统稳定性充分条件.在此基础上,分析得到该队列闭环系统的弦稳定性充分条件.最后,通过7辆车组成的队列系统对比仿真实验,验证该方法的优越性.展开更多
当前对抗训练(AT)及其变体被证明是防御对抗攻击的最有效方法,但生成对抗样本的过程需要庞大的计算资源,导致模型训练效率低、可行性不强;快速AT(Fast-AT)使用单步对抗攻击代替多步对抗攻击加速训练过程,但模型鲁棒性远低于多步AT方法...当前对抗训练(AT)及其变体被证明是防御对抗攻击的最有效方法,但生成对抗样本的过程需要庞大的计算资源,导致模型训练效率低、可行性不强;快速AT(Fast-AT)使用单步对抗攻击代替多步对抗攻击加速训练过程,但模型鲁棒性远低于多步AT方法且容易发生灾难性过拟合(CO)。针对这些问题,提出一种基于随机噪声和自适应步长的Fast-AT方法。首先,在生成对抗样本的每次迭代中,通过对原始输入图像添加随机噪声增强数据;其次,累积训练过程中每个对抗样本的梯度,并根据梯度信息自适应地调整对抗样本的扰动步长;最后,根据步长和梯度进行对抗攻击,生成对抗样本用于模型训练。在CIFAR-10、CIFAR-100数据集上进行多种对抗攻击,相较于N-FGSM(Noise Fast Gradient Sign Method),所提方法在鲁棒准确率上取得了至少0.35个百分点的提升。实验结果表明,所提方法能避免Fast-AT中的CO问题,提高深度学习模型的鲁棒性。展开更多
We introduce a novel model for robustness of complex with a tunable attack information parameter. The random failure and intentional attack known are the two extreme cases of our model. Based on the model, we study th...We introduce a novel model for robustness of complex with a tunable attack information parameter. The random failure and intentional attack known are the two extreme cases of our model. Based on the model, we study the robustness of complex networks under random information and preferential information, respectively. Using the generating function method, we derive the exact value of the critical removal fraction of nodes for the disintegration of networks and the size of the giant component. We show that hiding just a small fraction of nodes randomly can prevent a scale-free network from collapsing and detecting just a small fraction of nodes preferentially can destroy a scale-free network.展开更多
Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to enc...Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 61575197 and 61307018the K.C.Wong Education Foundation,the President Fund of University of Chinese Academy of Sciencesthe Fusion Funds of Research and Education of Chinese Academy of Sciences
文摘The principle of ptychography is applied in known plain text attack on the double random phase encoding （DRPE） system. We find that with several pairs of plain texts and cipher texts, the model of attack on DRPE can be converted to the model of ptyehographical imaging. Owing to the inherent merits of the ptyehographical imaging, the DRPE system can be breached totally in a fast and nearly perfect way, which is unavailable for currently existing attack methods. Further, since the decryption keys can be seen as an object to be imaged from the perspective of imaging, the ptychographical technique may be a kind of new direction to further analysis of the security of other encryption systems based on double random keys.
文摘当前对抗训练(AT)及其变体被证明是防御对抗攻击的最有效方法,但生成对抗样本的过程需要庞大的计算资源,导致模型训练效率低、可行性不强;快速AT(Fast-AT)使用单步对抗攻击代替多步对抗攻击加速训练过程,但模型鲁棒性远低于多步AT方法且容易发生灾难性过拟合(CO)。针对这些问题,提出一种基于随机噪声和自适应步长的Fast-AT方法。首先,在生成对抗样本的每次迭代中,通过对原始输入图像添加随机噪声增强数据;其次,累积训练过程中每个对抗样本的梯度,并根据梯度信息自适应地调整对抗样本的扰动步长;最后,根据步长和梯度进行对抗攻击,生成对抗样本用于模型训练。在CIFAR-10、CIFAR-100数据集上进行多种对抗攻击,相较于N-FGSM(Noise Fast Gradient Sign Method),所提方法在鲁棒准确率上取得了至少0.35个百分点的提升。实验结果表明,所提方法能避免Fast-AT中的CO问题,提高深度学习模型的鲁棒性。
基金Supported by the National Natural Science Foundation of China under Grant No 70501032.
文摘We introduce a novel model for robustness of complex with a tunable attack information parameter. The random failure and intentional attack known are the two extreme cases of our model. Based on the model, we study the robustness of complex networks under random information and preferential information, respectively. Using the generating function method, we derive the exact value of the critical removal fraction of nodes for the disintegration of networks and the size of the giant component. We show that hiding just a small fraction of nodes randomly can prevent a scale-free network from collapsing and detecting just a small fraction of nodes preferentially can destroy a scale-free network.
基金supported by the National Natural Science Foundation of China under Grant Nos. 61772009 and U1736112the Natural Science Foundation of Jiangsu Province under Grant Nos. BK20161511 and BK20181304
文摘Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.
