为解决SDN(software defined network,软件定义网络)架构下DDoS(distributed denial of service,分布式拒绝服务)攻击检测问题,提出基于贝叶斯ARTMAP的DDoS攻击检测模型.流量统计模块主要收集捕获到的流表信息,特征提取模块提取流表中...为解决SDN(software defined network,软件定义网络)架构下DDoS(distributed denial of service,分布式拒绝服务)攻击检测问题,提出基于贝叶斯ARTMAP的DDoS攻击检测模型.流量统计模块主要收集捕获到的流表信息,特征提取模块提取流表中的关键信息并获取关键特征,分类检测模块通过贝叶斯ARTMAP提取分类规则,并通过粒子群算法对参数进行优化,对新的数据集进行分类检测.仿真实验证明了模型所提取的5元特征的有效性,并且该模型与3种传统的DDoS攻击检测模型相比检测成功率提高了0.96%~3.71%,误警率降低了0.67%~2.92%.展开更多
Fault analysis is a frequently used side-channel attack for cryptanalysis.However,existing fault attack methods usually involve complex fault fusion analysis or computation-intensive statistical analysis of massive fa...Fault analysis is a frequently used side-channel attack for cryptanalysis.However,existing fault attack methods usually involve complex fault fusion analysis or computation-intensive statistical analysis of massive fault traces.In this work,we take a property-based formal verification approach to fault analysis.We derive fine-grained formal models for automatic fault propagation and fusion,which establish a mathematical foundation for precise measurement and formal reasoning of fault effects.We extract the correlations in fault effects in order to create properties for fault verification.We further propose a method for key recovery,by formally checking when the extracted properties can be satisfied with partial keys as the search variables.Experimental results using both unprotected and masked advanced encryption standard(AES)implementations show that our method has a key search complexity of 216,which only requires two correct and faulty ciphertext pairs to determine the secret key,and does not assume knowledge about fault location or pattern.展开更多
文摘为解决SDN(software defined network,软件定义网络)架构下DDoS(distributed denial of service,分布式拒绝服务)攻击检测问题,提出基于贝叶斯ARTMAP的DDoS攻击检测模型.流量统计模块主要收集捕获到的流表信息,特征提取模块提取流表中的关键信息并获取关键特征,分类检测模块通过贝叶斯ARTMAP提取分类规则,并通过粒子群算法对参数进行优化,对新的数据集进行分类检测.仿真实验证明了模型所提取的5元特征的有效性,并且该模型与3种传统的DDoS攻击检测模型相比检测成功率提高了0.96%~3.71%,误警率降低了0.67%~2.92%.
基金supported by the National Key R&D Program of China(No.2021YFB3100901)the National Natural Science Foundation of China(Nos.62074131 and 62004176).
文摘Fault analysis is a frequently used side-channel attack for cryptanalysis.However,existing fault attack methods usually involve complex fault fusion analysis or computation-intensive statistical analysis of massive fault traces.In this work,we take a property-based formal verification approach to fault analysis.We derive fine-grained formal models for automatic fault propagation and fusion,which establish a mathematical foundation for precise measurement and formal reasoning of fault effects.We extract the correlations in fault effects in order to create properties for fault verification.We further propose a method for key recovery,by formally checking when the extracted properties can be satisfied with partial keys as the search variables.Experimental results using both unprotected and masked advanced encryption standard(AES)implementations show that our method has a key search complexity of 216,which only requires two correct and faulty ciphertext pairs to determine the secret key,and does not assume knowledge about fault location or pattern.
