We argue that traditional identity-based systems from pairings seem unsuitable for designing group signature schemes due to the problem of key escrow. In this paper we first propose new ID-based public key systems wit...We argue that traditional identity-based systems from pairings seem unsuitable for designing group signature schemes due to the problem of key escrow. In this paper we first propose new ID-based public key systems without trusted PKG (Private Key Generator) from bilinear pairings. In our new ID-based systems, if the dishonest PKG impersonates an honest user to communicate with others, the user can provide a proof of treachery of the PKG afterwards, which is similar to certificate-based systems. Therefore, our systems reach the Girault’s trusted level 3. We then propose a group signature scheme under the new ID-based systems, the security and performance of which rely on the new systems. The size of the group public key and the length of the signature are independent on the numbers of the group.展开更多
Internet of Things(IoT)networks leverage wireless communication protocols,which adversaries can exploit.Impersonation attacks,injection attacks,and flooding are several examples of different attacks existing in Wi-Fi ...Internet of Things(IoT)networks leverage wireless communication protocols,which adversaries can exploit.Impersonation attacks,injection attacks,and flooding are several examples of different attacks existing in Wi-Fi networks.Intrusion Detection System(IDS)became one solution to distinguish those attacks from benign traffic.Deep learning techniques have been intensively utilized to classify the attacks.However,the main issue of utilizing deep learning models is projecting the data,notably tabular data,into an image.This study proposes a novel projection from wireless network attacks data into a grid-based image for feeding one of the Convolutional Neural Network(CNN)models,EfficientNet.We define the particular sequence of placing the attribute values in a grid that would be captured as an image.Combining the most important subset of attributes and EfficientNet,we aim for an accurate and lightweight IDS module deployed in IoT networks.We examine the proposed model using the Wi-Fi attacks dataset,called the AWID2 dataset.We achieve the best performance by a 99.91%F1 score and 0.11%false-positive rate.In addition,our proposed model achieved comparable results with other statistical machine learning models,which shows that our proposed model successfully exploited the spatial information of tabular data to maintain detection accuracy.展开更多
基金Supported by National Natural Science Foundation of China (No.60503006 and No.60403007) and Natural Science Foundation of Guangdong, China (No. 04205407).
文摘We argue that traditional identity-based systems from pairings seem unsuitable for designing group signature schemes due to the problem of key escrow. In this paper we first propose new ID-based public key systems without trusted PKG (Private Key Generator) from bilinear pairings. In our new ID-based systems, if the dishonest PKG impersonates an honest user to communicate with others, the user can provide a proof of treachery of the PKG afterwards, which is similar to certificate-based systems. Therefore, our systems reach the Girault’s trusted level 3. We then propose a group signature scheme under the new ID-based systems, the security and performance of which rely on the new systems. The size of the group public key and the length of the signature are independent on the numbers of the group.
文摘Internet of Things(IoT)networks leverage wireless communication protocols,which adversaries can exploit.Impersonation attacks,injection attacks,and flooding are several examples of different attacks existing in Wi-Fi networks.Intrusion Detection System(IDS)became one solution to distinguish those attacks from benign traffic.Deep learning techniques have been intensively utilized to classify the attacks.However,the main issue of utilizing deep learning models is projecting the data,notably tabular data,into an image.This study proposes a novel projection from wireless network attacks data into a grid-based image for feeding one of the Convolutional Neural Network(CNN)models,EfficientNet.We define the particular sequence of placing the attribute values in a grid that would be captured as an image.Combining the most important subset of attributes and EfficientNet,we aim for an accurate and lightweight IDS module deployed in IoT networks.We examine the proposed model using the Wi-Fi attacks dataset,called the AWID2 dataset.We achieve the best performance by a 99.91%F1 score and 0.11%false-positive rate.In addition,our proposed model achieved comparable results with other statistical machine learning models,which shows that our proposed model successfully exploited the spatial information of tabular data to maintain detection accuracy.
