The invention discloses an incremental learning-based traffic exception detection method and device, and a storage medium. The method comprises the steps of acquiring traffic data of a user terminal;detecting exception of the traffic data by using a pre-created traffic detection classifier in an exception detection device; and when abnormal data is detected, obtaining training sample data based on the abnormal data, and performing online training on the traffic detection classifier by using the training sample data. The generalization capability of the classifier is improved by diversifying the training samples.

Incremental learning-based traffic exception detection method and device, and storage medium

The invention discloses a log stream anomaly detecting method. The method comprises the steps of utilizing a detecting model to perform anomaly detection on log stream to be detected and judging whether the log stream to be detected is abnormal or not according to detection results, wherein the detecting model is obtained by training an initial model according to training log stream and an anomaly detecting algorithm; if the log stream to be detected has anomaly, judging whether the anomaly is a known threat or not; if the anomaly is not the known threat, updating the detecting model according to received anomaly rechecking information. The method can recognize the anomaly in the log stream and autonomously learn the new anomaly, not only recognizes the known threat, but also can learn unknown events and improves safety of a network environment. The invention further discloses a log stream anomaly detecting system which also has the beneficial effects.

Log stream anomaly detecting method and system

A DDoS attack detection system based on a back-propagation neural network algorithm comprises a data acquisition module, a data preprocessing module, a resource scheduling module, a rule base module,data analysis modules and a response module, wherein the data acquisition module is used to collect network traffics; the data preprocessing module is used to preprocess original network traffic data;the resource scheduling module is used to allocate the appropriate data analysis module for data analysis; the rule base module is used to filter the data with intrusion features; the data analysis modules are used to real-timely update rules of the rule base module; and the response module is used to detect intrusion behaviors and give responses and alarms. The DDoS attack detection system disclosed by the invention has the beneficial effects as follows: the accuracy of attack detection can be improved; the situation that a traditional detection method based on a feature detection algorithmcan only detect known attack modes and can helplessly process unknown attacks can be improved; and the shortcomings of slow convergence speed and low accuracy of a traditional back-propagation neuralnetwork algorithm can be improved.

DDoS attack detection system and method based on back-propagation neural network algorithm

The invention provides a method and a system for detecting document change and synchronization The method comprises the steps of creating a detection thread, a synchronized thread and a transmission object when a process of an application program is started; respectively obtaining database information in a client and database information in a server; respectively extracting document unique identifications and document change identifications which are preset for documents from the database information in the client and the server; comparing document unique identifications so as to obtain newly addition and deletion information of documents in the server; comparing the document change identifications so as to obtain revision information of the documents in the server; packaging the newly addition and deletion information and the revision information of the documents in the server so as to form a task data packet; transmitting the task data packet to the synchronized thread by utilizing the transmission object; processing the task data packet by the synchronized thread, and synchronizing the changed documents in the server to the client According to the method and the system, the document change in all specified directories can be detected, so that the loss of the document change information is avoided

Method and system for detecting document change and synchronization

The invention discloses a method and a system for performing multi-account backup on data of a public cloud storage system. The method comprises the following steps of S1, binding an account of a personal private cloud storage system with a plurality of public cloud storage accounts and a storage device with a wifi function; S2, traversing directories and file names in each public cloud storage account for the first time by the personal private cloud storage system, and after the traversal is finished, exporting and storing directory and file name data in a database; S3, generating a plurality of task groups by the directory and file name data in the database through the personal private cloud storage system, and waiting for the storage device with the wifi function to actively obtain the task groups; and S4, after the storage device with the wifi function is connected to the internet, automatically starting to download task data from each public cloud storage account according to the directories and the file names in the current task groups. According to the method and system, the content of a plurality of the cloud storage accounts can be intelligently and automatically backed up in the same storage device, thereby ensuring data security.

Method and system for performing multi-account backup on data of public cloud storage system

The invention relates to an intrusion detection independent analysis method in a cloud calculation environment. An intrusion detector is trained through an improved BP neural network; the intrusion detector detects preprocessed network data packages with abnormal network traffic in real time; the detected abnormal data is recognized by the intrusion detector, so that network intrusion behaviors of known types are recognized; and characteristics of network intrusion behaviors that cannot be recognized in type are extracted to be used as training samples for independent learning so as to provide sources for recognition of new types of network intrusion behaviors. The invention also relates to an intrusion detection system. The system comprises a data acquisition module, a data preprocessing module, an intrusion detector, a resource dispatching module, a response and warning module, a database and an error tolerance module. The system can perform detection and recognition on the network intrusion behaviors. According to the intrusion detection method and system, a new way for independent analysis and detection of network intrusion in the cloud calculation environment is created, the detection rate is high and the expansibility is good.

Intrusion detection independent analysis method and system in cloud calculation environment

The invention relates to an automatic cloud storage synchronous management system for a plurality of cloud storage service platforms and a method thereof. The automatic cloud storage synchronous management system comprises cloud storage service platforms, an account management module, a normal setting module, a file synchronizing module, an API control module, a file backup module and a log module. A user firstly selects a certain cloud storage service platform and logs the account management module for creating a cloud storage client. Then the normal setting module is used for performing system and network setting on the cloud storage client. Furthermore the API control module is called through the file synchronizing module for synchronously updating a local file and a cloud-end file, thereby realizing automatic storage and synchronization for the plurality of cloud storage service platforms. Secondly, the file backup module periodically compresses and encrypts a document file to be backed up and takes the document file back. Finally the log module records the execution state of the API control module in real time. The automatic cloud storage synchronous management system and the method thereof realize safety protection for the backup files which are stored at the cloud end.

Automatic cloud storage synchronous management system for a plurality of cloud storage service platforms and method thereof

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Intrusion detection independent analysis method and system in cloud calculation environment

Automatic cloud storage synchronous management system for a plurality of cloud storage service platforms and method thereof