6 results about "Extended field" patented technology

A flow suppression method is applied to meet the suppression requirement of data flow and avoid data packet loss. In the flow suppression method, when congestion occurs in the receiving side network device when processing data packets, the receiving side network device sends an extended PFC packet to the sending side network device to instruct the sending side network device to suspend sending data packets for a period of time. Moreover, the extended PFC packet uses two fields (an existing field and an extended field) to indicate the length of time for which the sending side network device suspends sending data packets, so that the extended PFC packet can instruct the sending side network device to suspend sending data packets for a longer period of time, thereby meeting the suppression requirement of data flow and avoiding data packet loss.

This application provides an extended field-of-view light sheet fluorescence microscopy imaging system, method, and product, including a beam generation unit, a light sheet generation unit, a sample carrying unit, and a signal detection unit. The beam generation unit is configured to phase-modulate an incident Gaussian beam based on a preset phase pattern to obtain a target Bessel beam. The light sheet generation unit is configured to generate a Bessel light sheet based on the target Bessel beam. The sample carrying unit is configured to position the carried sample in the scanning area of ​​the Bessel light sheet. The signal detection unit is configured to collect the fluorescence signal generated by the sample in the scanning area. This application utilizes a long depth-of-focus, diffraction-free beam as the illumination light in light sheet fluorescence imaging, which overcomes the technical bottleneck of traditional Bessel beam light sheet imaging, which cannot guarantee resolution while improving the imaging field of view. This allows for covering a larger sample area in a single exposure, thus increasing imaging speed.

Embodiments of the present specification provide a method and device for generating a check script for a target application, wherein the method for generating the check script comprises: obtaining TM metadata configured by a user. Identifying strong fields and weak fields from a target data table. Calling a parsing engine to parse field values of the weak fields to obtain extended fields corresponding to sub-fields in the weak fields, the field name of the extended field being used to identify the complete hierarchical path of the corresponding sub-field. Determining the strong fields and the extended fields as each target field in the target data table. Extracting code symbols and their annotation information from the business code of the target application. Inputting the code symbols and their annotation information into an intelligent agent, and letting the intelligent agent perform semantic parsing on the code symbols based on the annotation information to obtain corresponding business meanings. Matching the business meanings with each target field to establish an association relationship between the code symbols and each target field. Generating a check script by using a code generation platform based on the association relationship.

This invention discloses a Tor website identification method for backbone network scenarios. The method first employs a fast stream reassembly strategy based on a limited window to process the original data packets, achieving efficient reassembly of encrypted streams. Then, it extracts extended field information from the TLS handshake phase data packets, constructs TLS handshake field sequence features, and reconstructs TLS records based on the TLS record header. It then statistically analyzes the frequency of occurrence of different TLS record lengths to construct TLS record length frequency distribution features. Based on the joint discrimination results of these two types of features, it constructs a set of target Tor encrypted streams. After identifying the target Tor streams, it combines the parallel link transmission mechanism of Tor clients to perform global temporal alignment and fusion of unidirectional TLS record sequences from different parallel encrypted streams, reconstructing the unidirectional TLS record feature sequence transmitted by the website server. Based on this, it constructs a multi-dimensional Tor website access fingerprint from three dimensions: time, record length, and transmission scale, to characterize the traffic patterns of different Tor websites. Finally, it trains an offline identification model based on the constructed website fingerprint, generates a Tor website classifier, and deploys it in the backbone network environment to achieve reliable identification of online traffic. This invention can extract stable and highly discriminative Tor website fingerprints in backbone network scenarios, enabling continuous and reliable identification of target website access behavior.

The application relates to the technical field of network security, in particular to an IPv6 encrypted traffic advanced persistent threat attack identification method and system; the method comprises the following steps: extracting a cipher suite arrangement sequence, an extended field type set and a cipher library version identifier; performing sequence comparison and tolerance determination with a preset legal client variant fingerprint library to determine a suite arrangement coincidence level; screening out to-be-identified messages with a coincidence level lower than a preset legal threshold to generate a to-be-identified object set; and performing clustering analysis based on the arrangement feature vectors of the to-be-identified object set to identify a homologous concealed imitated traffic subset. In this way, the technical problem that the identification precision of a handshake fingerprint template and the overall identification accuracy are difficult to be considered in the prior art when dealing with the realistic scene of diversified client fingerprints in a signal creation environment is solved, and the accuracy and reliability of encrypted threat identification are improved.

This invention discloses an AI-native semantic cognition method and system, belonging to the interdisciplinary field of artificial intelligence and system software. The method includes: a semantic extension step, which adds extended fields such as semantic target identifiers, data flow roles, and tensor network anchor point identifiers to the native data structures in the program runtime environment, forming a semantically enhanced extended structure; a holographic semantic graph construction step, which performs unified graph representation on all extended structures, constructing a holographic semantic graph that integrates capability dependencies, semantic relationships, and tensor network anchor point information into a single data structure for each node, enabling the complete semantic context to be directly obtained when querying any node without cross-graph indexing; and a deterministic rhythmic scheduling step, which, based on a preset number of attention domains 'a' and granularity levels 'b', deterministically calculates the cognitive scheduling index D(n) = ((n-1) mod a) + 1 and G(n) = ((n-1) mod b) + 1 corresponding to the current clock cycle 'n', to reproducibly allocate AI cognitive resources to the corresponding attention domains and granularity levels. The system includes a semantic extension structure module, a holographic semantic graph module, an AI common core module, a semantic call bridge module, and a ghost cache module. This invention enables AI to accurately perceive program semantics, auditable cognitive scheduling based on deterministic rhythms, and secure online evolution with cognitive self-protection capabilities. It solves the problems of semantic gaps between existing AI systems and operating environments, lack of evolutionary security boundaries, blind spots in attention allocation, and fragmented semantic graph representations.