564results about How to "Accurate discovery" patented technology

The invention discloses a network worm detection and characteristic automatic extraction method and a network worm detection and characteristic automatic extraction system and belongs to the technical field of network safety. The method comprises the following steps of: 1) performing abnormal detection on captured network data packets, and dividing the data packets into suspicious network flow and normal network flow according to detection results; 2) storing the suspicious network flow in a suspicious flow pool, and storing the normal network flow in a normal flow pool; 3) clustering the network flow in the suspicious flow pool and the normal flow pool, and extracting a characteristic signature; and 4) updating the extracted characteristic signature in a network attack database, and detecting the network worm. The system comprises an abnormal detection subsystem, a characteristic extraction subsystem, a network attack characteristic database, and a misuse detection system. The methodand the system can more accurately and timely discover the network worm, can automatically extract the worm characteristics and update the attack characteristic database of the existing misuse detection system. Therefore, the aim of suppressing worm propagation is really fulfilled.

The invention provides a mobile data traffic package recommendation algorithm based on user historical data according to data mining analysis technology. The mobile data traffic package recommendation algorithm comprises the following steps of: 1) a target user finding period comprising the processes of a, acquiring a processed generated data set which comprises a training set and a prediction set, b, executing a random forest classification algorithm for finding a latent data traffic package improving user as a target user, and c, ending; 2), a data traffic package recommendation period comprising the process of a, acquiring a processed generated prediction set, b, executing a K-means clustering algorithm for obtaining a slightly similar user cluster, c, obtaining the target user obtained in the process 1)-b, d, executing a TopN recommendation algorithm on the target user in a same cluster according to a similarity function of the user, and e, ending. The mobile data traffic package recommendation algorithm is used for finding the latent user with a latent data traffic improvement requirement according to data mining technology and executing a recommended plan on the user. Compared with a traditional method, the mobile data traffic package recommendation algorithm has advantages of higher accuracy, higher efficiency, simple realization, low cost, etc.

The invention relates to an account security technology, and discloses a method and system for identifying computer risks based on account clustering. In the method disclosed by the invention, clustering is carried out according to a pre-set characteristic attribute; account characteristic data is divided into multiple categories; furthermore, whether the account number in various categories after division is greater than a first threshold value or not is judged, such that a potential batch suspicious account is identified; therefore, risks are avoided effectively; in addition, judgement of the suspicious account is completed through an offline server; furthermore, a service permission table is generated; an online server can find the suspicious account in time according to the service permission table and forbid the suspicious account to use corresponding services; therefore, the online risk identification speed is enhanced; and better services are provided.

The invention relates to a microblog hype group discovering method based on maximum frequent item set mining. Microblog hype groups are effectively discovered, and false and malicious hype is avoided. The method comprises the steps that the correlation of a hype microblog is used as a clue, and an account set participating in hype microblog transmission is obtained based on the crawler technology or a microblog public open platform; single microblogs are used as transactions, accounts participating in microblog transmission are used as items, and a hype microblog transaction database is built; for transactions, corresponding to a microblog set to be detected, in the transaction database, the maximum frequent item sets contained in the transactions are found, the overlapping ratio of the maximum frequent item sets is calculated, small-scale item sets are merged into large item sets, the intersection frequency is reduced, whether the transactions comprise a certain item or not is judged through the binary search method when intersection is obtained between the transactions, the maximum frequent item set mining efficiency is improved, and microblog hype groups are discovered. The microblog hype group discovering method based on maximum frequent item set mining is simple, and can accurately discover malicious microblog hype groups and avoid negative influences on the society.

The invention discloses a dynamic detection method for a cross-site forged request, which comprises the following steps: collecting HTTP request information; analyzing whether a request is a CSRF suspect request or not according to the collected information; generating a test case aiming at the suspect request and finding out all suspect parameters contained by the suspect request; using the suspect parameters to generate a plurality of forged requests and generating a test case for each forged request; when an environment in which the suspect request is generated recurs, executing the forged request corresponding to each test case; detecting CSRF vulnerabilities; and according to the suspect request, the execution information of the suspect request, the forged requests and the execution information of the forged requests, analyzing whether the forged requests find the CSRF vulnerabilities in Web application or not, forming a report and helping a Web application developer to repair the vulnerabilities. Since the dynamic detection method is used for detecting the CSRF vulnerabilities, the CSRF vulnerabilities in the Web application can be rapidly and accurately found out at low cost.

The invention relates to an anti-theft system for automobiles and discloses an anti-theft system for automobiles in parking lots. The anti-theft system comprises a cloud platform server, a plurality of parking lots and a plurality of automobile owner terminal devices, wherein the parking lots and the automobile owner terminal devices are in data exchange with the cloud platform server via the network, and each automobile owner terminal device at least comprises a cellphone. The invention further discloses an anti-theft method for automobiles in the parking lots. The anti-theft method includes S10, registering members; S20, setting member owners; S30, automobiles entering the parking lots; S40, checking for preventing fake license plates; S50, banning for anti-theft of the automobiles; S60, unbanning and letting the automobiles go; and S70, letting the automobiles driven out of the parking lots. By the anti-theft system and the anti-theft method, the automobiles with fake license plates can be accurately found and anti-theft effect of the automobiles can be realized.

The invention provides a compensation type gas sensor and a humiture compensation method thereof. The compensation type gas sensor comprises a microprocessor circuit, a gas sensor, a temperature sensor, a humidity sensor, a gas concentration signal processing circuit, a temperature signal processing circuit, a humidity signal processing circuit and a power supply circuit. The humiture compensation method comprises the following steps of: creating a compensation factor searching database; obtaining a gas concentration measured value C0, a temperature measured value T and a humidity measured value H through actual measurement; searching a compensation factor @ corresponding to the gas concentration measured value C0, the temperature measured value T and the humidity measured value H from the compensation factor searching database according to the gas concentration measured value C0, the temperature measured value T and the humidity measured value H; and obtaining a gas concentration true value C1 of the gas sensor by multiplying the gas concentration measured value C0 with the compensation factor @ according to the searched compensation factor @. The compensation type gas sensor provided by the invention has the advantages of being high in detection accuracy, reliable in performance, and suitable for the high-temperature high-humidity environment detection; and the humiture compensation method provided by the invention has the advantages of being simple and practical, and beneficial for increasing the detection accuracy of the gas sensor.

The invention discloses a testing method and system, a testing server, a testing terminal and a storage medium. The method comprises the following steps that according to a to-be-executed testing script, a testing task is created; the testing task is sent to the corresponding testing terminal, wherein the testing task is used for triggering the testing terminal to run a to-be-tested program according to the testing script and release the running data generated in the to-be-tested program running process into a corresponding subject; the running data received by the subscribed subject is obtained through a subscriber object; the received running data is sent to a front-end user side, wherein the running data is used for triggering the front-end user side to display the running data on a display interface of the subject corresponding to the running data. Based on the testing method, visual automatic regression testing can be achieved, and the testing efficiency is improved.

The invention discloses an intelligent analysis system for all-media detection and monitoring big data behaviors and relates to an all-media monitoring system. The intelligent analysis system comprises a public opinion collection layer, a public opinion processing layer and a public opinion presentation layer, wherein the public opinion collection layer is connected with the public opinion processing layer; the public opinion processing layer is presented by the public opinion presentation layer; in the public opinion collection layer, a distributed and oriented collection engine collects news, forums, blogs, micro blogs, print media, questions and answers and other public opinion information from the Internet, and stores the information into a distributed database and a file system. The intelligent analysis system realizes data content analysis, semantic analysis and descriptive analysis on media monitoring big data, builds a data analysis model based on media, a media big data structure and a content analysis multilevel description method, realizes functions of a super-large scale media data content conceptual analysis model and is an intelligent data behavior analysis system for understanding all-media data content.

The invention belongs to the field of pipeline detection, and particularly relates to a multilayer buried pipeline leakage source locating device and method based on acoustic emission inspection. The locating device is characterized in that a first waveguide rod and a second waveguide rod are fixed to the two sides of a leakage source respectively; the lower end of a first piezoelectric acceleration sensor and the lower end of a second piezoelectric acceleration sensor are bonded to the surfaces of the first waveguide rod and the second waveguide rod respectively; the upper end of the first piezoelectric acceleration sensor and the upper end of the second piezoelectric acceleration sensor are connected with a first preamplifier and a second preamplifier respectively through wires; then signals are transmitted to a first data acquisition module and a second data acquisition module; the signals are transmitted to an A/D converter through the two data acquisition modules to be converted to digital signals; the A/D converter transmits the digital signals to a host, and the host determines the position of the leakage source of a pipeline finally. According to the multilayer leakage source locating method, local locating and accurate locating are combined, local locating based on signal amplitude damping is adopted, accurate locating of the pipeline leakage source under a complex working condition is achieved finally based on acoustic emission inspection, and the method is suitable for locating of leakage of the pipeline under a buried condition.

The invention discloses a static detection method for privacy information disclosure in mobile applications. The method comprises the steps as follows: firstly, the completeness of codes is checked, if the codes are incomplete, preparatory work is performed on source codes, state machine description files corresponding to the privacy disclosure are loaded, related state machine information is obtained, the source codes are compiled to obtain detailed information of classes, functions and the like, pre-analysis is performed on the source codes, basic data structures such as abstract syntax trees and the like are generated, and call relations among the functions are obtained; and then detection and analysis is performed in units of the functions, state machine instances are created for all state machines with associated methods in the state machines, state machine instance iteration is performed on control flow diagrams corresponding to the functions, when the state machine instances are in error states, errors are reported, after detection is finished, the detected errors are checked manually, and detection results are confirmed. With the adoption of the method, the privacy disclosure codes existing in application programs of different operating system platforms can be effectively detected, so that the privacy information disclosure of users can be effectively prevented.

The invention discloses a defect quantified comprehensive safety judgment method for an on-service pressure container. The method comprises the steps of detecting a defect of the on-service pressure container by a magnetic memory detection method, and quantifying the defect by a calculation formula; performing planar defect breakage evaluation and planar defect fatigue evaluation on the on-service pressure container according to a magnetic memory detection result; constructing a comprehensive judgment matrix by a fuzzy comprehensive judgment system, calculating a total damage rate according to the damage rate, caused by each ineffectiveness factor, on the pressure container and a weight of the influences on the safety of the pressure container, determining a relation of the influences, and making comprehensive safety judgment. The defect quantified comprehensive safety judgment method for the on-service pressure container is high in reliability and high in operability, and an evaluation result can objectively and really reflect actual situations of engineering.

The invention discloses a method for detecting the anti-seepage effect of an anti-seepage film, belonging to the anti-seepage detection field of anti-seepage films. The method comprises the following steps: adopting a high-pressure pulse power supply to apply electric potentials onto the upper side and the lower side of the anti-seepage film by current electrodes the positions of which are fixed; arranging a fixed electrode and a movable electrode in an upper detection region of the anti-seepage film, wherein the position of the fixed electrode is fixed; and distributing detection points at 1-5m *1-5m intervals by the movable electrode. In measurement, a high-pressure pulse is applied onto the current electrodes to measure an electric potential difference between the movable electrode and the fixed electrode until all measuring points are measured; and the distribution of the electric potential differences is distorted in loophole positions so as to judge the existence and the positions of leakage. The invention is a nondestructive measurement method and has high detection precision and simple and convenient operation.

The invention discloses a WSN abnormity detection method and system based on artificial immunization and k-means clustering. The method comprises that S1) original monitoring data collected by WSN nodes is obtained to form a time sequence, the time sequence is normalized, compression and dimension reduction are carried out on the normalized sequence, and the mean value and variance of each sequential segments in the compressed sequence are calculated; S2) the Euclidean distance between node data and each cluster head is calculated, and an artificial immunization algorithm is used to search an optimal initial cluster head set for K-means classification; S3) whenever new data is distributed into a corresponding cluster, iterative update is carried out on the cluster head value of the cluster till the amount of all data in the cluster does not change; and S4) the WSN determines abnormity according to the amount of data in the cluster in a K-means clustering result. According to the invention, abnormity information in monitoring data can be discovered accurately, the instantaneity and reliability of abnormity event detection of the WSN are improved, and energy and communication bandwidth of the WSN are greatly reduced.

The invention relates to a current change rate-based coal mine power grid short-circuiting fault quick judging device and method. The method includes the following four stages of judgment calculation: stage 1, current first-order derivative calculation; stage 2, current first-order derivative zero point crossing judgment; stage 3, current first-order derivative judgment; and stage 4, current second-order derivative calculation and judgment. The method specifically includes the following steps that: the current change rate of a coal mine power grid line is calculated uninterruptedly; whether a first-order derivative crosses a zero point is judged, if the first-order derivative crosses the zero point, the method enters the stage 4, current second-order calculation is started; if the first-order derivative does not cross the zero point, the method enters the stage 3, the first-order derivative is compared with a previous current change rate calculation result, if the current first-order derivative exceeds a set change range, it is judged that a short-circuiting fault occurs, otherwise, the method enters the stage 1, first-order derivative calculation is further executed; and a current second-order derivative is calculated, and is compared with a previous current change second-order derivative, if the current second-order derivative exceeds a set range, it is judged that a short-circuiting fault occurs, and corresponding operation is carried out, otherwise, the method returns to the stage 1. The current change rate-based coal mine power grid short-circuit fault quick judging device and method provided by the invention can quickly and accurately find faults at the moment when short-circuiting occurs.

The invention discloses a method for determining whether passages issued by network users have copy relations or not. The method includes: acquiring time probability distribution obeyed by time intervals of two passages with clear forwarding relations; deducing time probability distribution obeyed by time intervals of two passages with copy relations according to the acquired time probability distribution; setting a range which needs to be satisfied by time intervals of the two passages with copy relations according to the deduced time probability distribution; for optional two passages whose time intervals are in the range, calculation the similarity of the two; and determining whether the two passages have copy relations according to the similarity.

The invention discloses a method and a device for automatically discovering new words from a document set. A template acquisition unit acquires one or more templates; a word extraction unit extracts words matched with all templates of the one or more templates from the document set; a candidate template set adding unit selects at least a part of templates from the one or more templates and adds the part of templates to a candidate template set; a candidate word set adding unit selects at least a part of words from the words matched with all the templates of the one or more templates and adds the part of words to a candidate word set; a new word set adding unit sequences candidate words in the candidate word set according to the templates in the candidate template set, and adds a certain number of candidate words to a new word set according to the sequence. Compared with the prior art, by adopting the method and the device, new words can be effectively discovered.