Abstract: The present disclosure relates to the technical field of Internet, in particular to a method for measuring network international outlet interfaces of a designated area. The method includes the following steps: acquiring a designated collection of routing interface paths and area location information of IP addresses of routing interface nodes; dividing the collected routing interface paths into critical hop complete paths and critical hop missing paths; determining whether a routing interface path is a critical hop complete path; using a 2-tuple to identify network international outlet interfaces of the routing interface path; and counting the quantity of the network international outlet interfaces of the measured area.

Abstract: The invention discloses a weighted heterogeneous graph-oriented malicious behavior identification method, system and storage medium. The method comprises the following steps: constructing an inductive graph neural network model. The inductive graph neural network model comprises a subgraph extraction module, a plurality of feature vector generation and fusion modules and a classification learning module; performing training and learning for the inductive graph neural network model, extracting subgraphs, learning the latent vector representation of nodes in the subgraphs, obtaining a plurality of subgraph feature vectors corresponding to the subgraphs, and fusing a plurality of subgraph feature vectors. The node feature vector obtained by fusion is used for classification learning in the classification learning module; using the trained inductive graph neural network model for malicious behavior identification.

Abstract: An APT organization identification method, system and storage medium based on a stacking ensemble are provided, the method comprising: using a TF-IDF algorithm combined with an n-gram to extract and vectorize behavior features from malware samples to form a malicious behavior vector feature set; based on the malicious behavior vector feature set, calculating correlations between features and chi-square values between the features and categories, performing screening twice on the malicious behavior vector feature set to obtain an improved low-dimensional feature subset data; constructing a multi-model fusion stacking ensemble, learning an APT organization identification model, using the APT organization identification model to perform an identification on new ATP attacks.

Abstract: A method for certificate transaction validation of a blockchain-based resource public key infrastructure aims to avoid security threats caused by conflicts or illegal transactions during transactions and improve security. A technical solution is as follows: constructing a resource public key infrastructure RPKIB system composed of a resource issuer, a resource transaction application client, a resource receiver, a blockchain network and a validation node; designing operations of a resource certificate and route origin authorization ROA as transactions, submitting operations of various resource transactions initiated by a resource issuer as transactions to the blockchain network, running, by the validation node, a smart contract to verify the transactions, and distinguishing whether the operations are malicious behaviors or normal operations of an authority.

Abstract: The present disclosure provides a multimodal fine-grained mixing method and system, a device, and a storage medium. The method includes: extracting data features from multimodal graphic and textual data, and obtaining each composition of the data features, the data features including a visual regional feature and a text word feature; performing fine-grained classification on modal information of each composition of the data features, to obtain classification results; and performing inter-modal and intra-modal information fusion on each composition according to the classification results, to obtain a fusion feature. The method enables a multimodal model to utilize a complementary characteristic of the multimodal data, with no influence by irrelevant information.

Abstract: The present disclosure provides an anomaly detection method and apparatus for multi-type data. According to the anomaly detection method for multi-type data, an adversarial learning network is trained, so that a generator in the adversarial learning network fits a distribution of a normal training sample and learns a potential mode of the normal training sample, to obtain an updated adversarial learning network, an anomaly evaluation function in the updated adversarial learning network is constructed according to a reconstruction error generated during training, and the updated adversarial learning network is constructed into an anomaly detection model, to perform anomaly detection on inputted detection data by the anomaly detection model, to obtain an anomaly detection result. A mode classifier is introduced to effectively resolve difficult anomaly detection when a distribution of detected data is similar to that of normal data, further improving the accuracy of anomaly detection.

Abstract: The present disclosure provides an anomaly detection method and apparatus for multi-type data. According to the anomaly detection method for multi-type data, an adversarial learning network is trained, so that a generator in the adversarial learning network fits a distribution of a normal training sample and learns a potential mode of the normal training sample, to obtain an updated adversarial learning network, an anomaly evaluation function in the updated adversarial learning network is constructed according to a reconstruction error generated during training, and the updated adversarial learning network is constructed into an anomaly detection model, to perform anomaly detection on inputted detection data by the anomaly detection model, to obtain an anomaly detection result. A mode classifier is introduced to effectively resolve difficult anomaly detection when a distribution of detected data is similar to that of normal data, further improving the accuracy of anomaly detection.

Abstract: The present disclosure provides a multimodal fine-grained mixing method and system, a device, and a storage medium. The method includes: extracting data features from multimodal graphic and textual data, and obtaining each composition of the data features, the data features including a visual regional feature and a text word feature; performing fine-grained classification on modal information of each composition of the data features, to obtain classification results; and performing inter-modal and intra-modal information fusion on each composition according to the classification results, to obtain a fusion feature. The method enables a multimodal model to utilize a complementary characteristic of the multimodal data, with no influence by irrelevant information.

Abstract: The disclosure discloses a method for bidirectional authorization of a blockchain-based resource public key infrastructure, aiming at solving security threat problems that a legal BGP route is illegal and a legal IP address is blocked caused by malicious operations.

Abstract: The disclosure disclosures a blockchain-based verifiable inter-domain routing validation method, which includes: constructing a blockchain-based verifiable inter-domain routing system consisting of a verifiable inter-domain routing and a routing behavior validation subsystem; constructing, by a sender router R1, a routing behavior validation terminal of an autonomous domain to which the R1 belongs, and the routing validation blockchain system, a routing evidence and a routing evidence validation proposal, validating and endorsing the proposal, determining whether the proposal satisfies an endorsement policy, generating a routing evidence transaction, conducting consensus ordering on the transaction and updating a routing validation blockchain; and constructing, by a receiver router T, a routing behavior validation terminal of an autonomous domain to which the T belongs, and the routing validation blockchain system, a routing request validation message and retrieving whether a routing evidence corresponding to

Abstract: The disclosure disclosures a blockchain-based verifiable inter-domain routing validation method, which includes: constructing a blockchain-based verifiable inter-domain routing system consisting of a verifiable inter-domain routing and a routing behavior validation subsystem; constructing, by a sender router R1, a routing behavior validation terminal of an autonomous domain to which the R1 belongs, and the routing validation blockchain system, a routing evidence and a routing evidence validation proposal, validating and endorsing the proposal, determining whether the proposal satisfies an endorsement policy, generating a routing evidence transaction, conducting consensus ordering on the transaction and updating a routing validation blockchain; and constructing, by a receiver router T, a routing behavior validation terminal of an autonomous domain to which the T belongs, and the routing validation blockchain system, a routing request validation message and retrieving whether a routing evidence corresponding to

Abstract: The disclosure discloses a method for bidirectional authorization of a blockchain-based resource public key infrastructure, aiming at solving security threat problems that a legal BGP route is illegal and a legal IP address is blocked caused by malicious operations.

Abstract: A method for certificate transaction validation of a blockchain-based resource public key infrastructure aims to avoid security threats caused by conflicts or illegal transactions during transactions and improve security. A technical solution is as follows: constructing a resource public key infrastructure RPKIB system composed of a resource issuer, a resource transaction application client, a resource receiver, a blockchain network and a validation node; designing operations of a resource certificate and route origin authorization ROA as transactions, submitting operations of various resource transactions initiated by a resource issuer as transactions to the blockchain network, running, by the validation node, a smart contract to verify the transactions, and distinguishing whether the operations are malicious behaviors or normal operations of an authority.