19 results about "Single session" patented technology

The invention discloses an Internet of Things device anti-quantum password migration method based on a national cryptographic algorithm, and relates to the field of data security, the method comprises the following steps: configuring a Hash agility module taking a national cryptographic SM3 as a default algorithm, and dynamically switching to an anti-quantum or compatibility alternative algorithm based on monitoring; carrying out identity authentication and temporary key negotiation by adopting SM2, and generating a key pair only used for a single session; deriving a session key based on the key pair, and adopting a differential double-layer signature verification mechanism according to the data security level; for firmware updating, a differential package is generated through function level differential analysis, and atomic updating and rollback are achieved through A / B system partition. According to the method, quantum computing threats are effectively resisted, national security compliance and forward security are ensured, the volume of an update package is remarkably reduced through a resource optimization technology, memory occupation is reduced, verification efficiency is improved, and the method is particularly suitable for resource-limited Internet of Things equipment.

The present invention addresses the problem of providing a flavor-generating article that can emit a caramel-like aroma and generate a gradual change in flavor during a single session.　This flavor-generating article includes a flavor-generating segment. The flavor-generating segment includes a first sheet containing a sugar and a second sheet containing nicotine. The first sheet contains (A) 5-60 wt% of the sugar, (B) 5-20 wt% of a first binder, (C) 10-60 wt% of a first aerosol source, and (D) 10-70 wt% of fibers.

A device captures, at the time of authentication to a secured session, secondary authentication data of the user that has authenticated using primary authentication credentials. Then, during the session, the system is caused to re-authenticate the user using the secondary authentication credentials (such as original and current user's face images). The system actively monitors the face visible to a camera of the computing device. The system compares the current face to the face image captured at the time of authentication. If the system fails to detect the same face captured initially at the time of authentication, then the system automatedly ends or otherwise locks the session to secure that session from an unauthorized user. Accordingly, the system does not rely merely upon initial authentication for an entire session, but rather reauthenticates the user during a single session in order for the session to be permitted to continue.

The described techniques address issues related to compatibility and cost-effectiveness of in-vehicle networks. The described techniques may utilize security protocols such as MACsec, for example, without the need to exchange separate key agreement messages and, consequently, meet the stringent starting time requirements for real-time control systems. Additionally, the described techniques may implement a secure channel multiplexing scheme that utilizes a session key management system to enable the use of a single secure channel at the endpoint (e.g. at each transmitting and receiving node) while supporting the implementation of multiple secure channels within a real-time control system. This advantageously allows for a significant reduction in the memory required by each node to store copies of session keys for each secure channel, as only a single session key needs to be stored locally by each node per secure channel.

The invention relates to the related field of user data screening, and discloses a data pre-management method and system based on feature learning, and the method comprises the steps: monitoring and recording a content browsing session of a user, thereby carrying out the judgment of individual behavior features, carrying out the pre-screening of a large amount of session data, and improving the user experience. Noise data useless for user content preference judgment is pre-screened out, so that the signal-to-noise ratio of a database in subsequent user content preference judgment is improved, evaluation efficiency and accuracy are optimized, and compared with an existing noise data screening mode based on content judgment session preference, the noise data screening method has the advantages that the noise data screening efficiency is improved. The noise screening mode based on behavior characteristics can more accurately avoid the situation that screening is inaccurate due to the fact that multiple content topics exist in a single session.

A device captures, at the time of authentication to a secured session, secondary authentication data of the user that has authenticated using primary authentication credentials. Then, during the session, the system is caused to re-authenticate the user using the secondary authentication credentials (such as original and current user's face images). The system actively monitors the face visible to a camera of the computing device. The system compares the current face to the face image captured at the time of authentication. If the system fails to detect the same face captured initially at the time of authentication, then the system automatedly ends or otherwise locks the session to secure that session from an unauthorized user. Accordingly, the system does not rely merely upon initial authentication for an entire session, but rather reauthenticates the user during a single session in order for the session to be permitted to continue.

Embodiments of the present disclosure are directed to systems and methods for improved identification and resolution of conflicting session information, such as when multiple session information entries are associated with a single session identifier. By communicating timestamps with the session information deposited in the NF component, the NF component may determine which session information is relevant to the request or which session information is stale and should be removed from its dataset.

Embodiments of the present disclosure disclose information generation methods, devices, electronic equipment and computer readable media. A specific embodiment of the information generation method comprises: obtaining a pre-constructed graph model, wherein the graph model represents the association relationship between a first user set, a second user set and an item set; generating first data according to each node and each edge associated with the node representing a first target user in the first user set in the graph model; obtaining second data of the first target user performing a second value operation on the item set; and generating first number information of the first target user performing a second value operation on the target item in a single session at a future predetermined time according to the first data and the second data. The embodiment efficiently and accurately generates the first number information of the first target user performing the second value operation on the target item in a single session at a future predetermined time by introducing the pre-constructed graph model.

Embodiments of the present disclosure are directed to systems and methods for improved identification and resolution of conflicting session information, such as when multiple session information entries are associated with a single session identifier. By communicating timestamps with the session information deposited in the NF component, the NF component may determine which session information is relevant to the request or which session information is stale and should be removed from its dataset.

A system or method for managing and tracking vehicle movements within a managed facility. The system captures a first image of a vehicle by a first camera at a first location, associates the first image with a first event identifier, and applies a vehicle identification model to determine an identification of the vehicle. Similarly, a second image is captured by a second camera as the vehicle continues through the facility, linked to a second event identifier. In response to determining that both images are identified as a same vehicle, both events are associated with a single session. The system then constructs a session timeline based on these events.

The purpose of the invention is to provide a secure and efficient method of identity verification for customer service agents and callers. The system enables businesses to securely assign customer service assignments to their agents and enables customers to verify the identity of the customer service agent who contacts them. The invention aims to prevent fraud, safeguard customer privacy, and prevent deceitful persons or entities from posing as legitimate business representatives to extort money or other benefits from customers. This invention streamlines the identity verification process for businesses and their customers, and enables caller introduction, purpose, and verification to be achieved in a single session.

The invention provides a new energy automobile charging safety data processing method based on machine learning. The new energy automobile charging safety data processing method comprises the steps that a cross-session tracking unit is constructed for multiple pairs of adjacent charging sessions; from a cross-session tracking unit, a reproduction trace type physical degradation feature capable of representing accumulative degradation in the connector is extracted, and an evolution track reflecting monotone increasing of the degradation feature along with time is constructed; generating a fatigue accumulation label for quantifying the internal fatigue accumulation degree of the connector contact based on the evolution trajectory; according to the grade of the fatigue accumulation label, a differentiated advanced intervention strategy is mapped and generated; according to the method, an intervention strategy is issued to a station operation and maintenance side for execution in advance, an intervention effect is verified based on recollected charging data after the strategy is executed, if a verification result shows that degradation is not effectively inhibited, the intervention strategy is upgraded, the limitation of single session analysis is broken through, cross-session data continuous tracking is realized, and an internal accumulative degradation trend can be accurately identified.

The invention discloses a crawler behavior recognition method and device, electronic equipment and a storage medium. The method comprises the following steps: reading a server network request log to obtain log data, screening the log data according to network request time, and determining target log data; grouping at least two network requests contained in a single session according to log information obtained by segmenting the target log data, and extracting log features of each network request group; clustering each network request group by adopting a subspace log clustering algorithm and determining a log clustering result; and determining the internal feature density of each network request group according to the log clustering result, and identifying the crawler behavior according to the internal feature density. By the adoption of the scheme, the technical defect that an existing crawler interception technology is prone to being pointedly broken is overcome, operation and maintenance personnel are assisted to efficiently and accurately recognize web crawler behaviors and take countermeasures, and safety and stability of network resources are guaranteed.

The invention provides a loop task processing method and device, electronic equipment and a storage medium. According to the method, a loop task is split into a plurality of independent sub-tasks which can be executed in parallel through a pre-trained first large language model, and a sub-task list is constructed. And generating a sub-session of each sub-task through a local loop execution component deployed in the agent, and promoting the second large language model to execute the corresponding sub-task through the sub-session. And one sub-session corresponds to one sub-task, and the second large language model can accurately determine the task to be executed currently according to the sub-session, so that the accuracy of the whole task is guaranteed. And the local loop execution component circularly traverses the whole sub-task list according to the sub-response of each sub-task by the second large language model to ensure that each sub-task is completely executed without omission. The method effectively solves the problem that a large language model cannot determine a task needing to be executed currently due to the fact that the context of a single session is too long.

The invention relates to the technical field of communication, and particularly provides a VNF (Virtual Network Function) instance migration method, a session service system and a session processing method, and the method comprises the steps: determining a to-be-migrated target VNF instance, a first network element cluster where the target VNF instance is currently located, and a second network element cluster undertaking the migrated target VNF instance; sending an instance migration instruction to a first main slow path network element in the first network element cluster, wherein the first main slow path network element deploys the target VNF instance; and adding a first target port number allocated for a target VNF instance on each fast path network element in the second network element cluster to a target selectable port number set associated with the target VNF instance, setting the priority of the first target port number to be the highest, and setting the priority of at least one second target port number to be the lowest, the second target port number is a port number allocated to a target VNF instance deployed for each fast path network element in the first network element cluster; according to the session migration method and device, the influence of single session migration on other sessions is eliminated, and the connection reliability of the sessions in the session migration process is improved.

The invention relates to the technical field of computers, in particular to an intelligent data processing method based on large model atomization packaging and batch processing arrangement, which comprises the steps of constraint set construction, constraint treatment and verification, target constraint set determination, flow description generation and batch processing arrangement and controlled output. According to the method, the executable constraint set is generated by inputting the constraint configuration submitted by the user and is included in the configuration management, so that the constraint is promoted from a single session prompt to a reusable configuration object, the operation cost caused by cross-session and cross-task repeated setting of the constraint is reduced, and the sustainable use capability of the constraint in a platform processing task is improved.

This invention belongs to the field of brainprint recognition technology in brain-computer interfaces, and discloses an online brainprint recognition method for cross-session scenarios. The method includes: collecting EEG data from K users in a single session; dividing each trial into non-overlapping EEG segments of length T; performing sliding window processing on the EEG segments at S different dynamic window scales to generate S sets of datasets at different dynamic window scales; offline training M different random seed models using each set of dynamic window scale datasets to obtain M brainprint recognition models; in a second session, inputting the online received data of length T after sliding window processing at the corresponding scale into the corresponding brainprint recognition model for user identity prediction; averaging and then weighting the prediction results to obtain the user identity prediction result, thus achieving online brainprint recognition across sessions. This invention improves the accuracy, robustness, and recognition speed of cross-session EEG signal identity recognition.

The application relates to the field of user data screening, and discloses a data pre-management method and system based on feature learning, which monitors and records the content browsing sessions of users, judges individual behavior features, pre-screens a large amount of session data, pre-screens noise data useless for user content preference judgment, improves the signal-to-noise ratio of a database in subsequent user content preference judgment, optimizes evaluation efficiency and accuracy, and compared with the existing noise data screening mode based on content judgment session preference, the noise screening mode based on behavior features can more accurately avoid the inaccurate screening caused by multiple content themes in a single session.