36 results about "Password strength" patented technology

The invention provides a password strength real-time evaluation method and device. The method comprises the following steps: training a polynomial naive Bayesian model through a password data set, wherein the password data set comprises a cracked weak password sample and a verified strong password sample; responding to a trigger event of password input by the user, and extracting character-level features and semantic features of the password input by the user; respectively generating sub-feature vectors according to the character-level features and the semantic features, and weighting the sub-feature vectors to obtain feature vectors; scoring the feature vector by using a trained polynomial naive Bayesian model to obtain a password strength score; and determining a password strength grade according to the password strength score. According to the method provided by the invention, the password strength can be evaluated in real time, and the accuracy of password security evaluation is improved.

The invention belongs to the field of password strength detection, and particularly relates to an intelligent password strength detection system and method based on exhaustion algorithm optimization, and the system comprises a receiving module, an analysis module, a risk judgment module and a strength generation module. According to the method, traditional exhaustive traversal is optimized through probability-guided brute force cracking simulation analysis, multi-source implicit weak password feature extraction is combined, weights of two analysis results are dynamically fused by using real-time attack data, and a dynamic comprehensive risk value is generated; meanwhile, the system carries out real-time comparison through a centralized weak password dictionary database, and can automatically trigger asynchronous batch tracing detection on historical passwords after the dictionary is updated. And finally, the system integrates the dynamic risk value and a dictionary judgment result, and outputs an accurate strength grade and a risk report. According to the method, the problems of low traversal efficiency, dimension explosion and difficulty in historical password tracing of a traditional method are effectively solved, and the real-time performance, the accuracy and the scene adaptability of detection are remarkably improved.

The invention provides a multi-strategy fusion password detection method and system and a medium, and relates to the technical field of data processing.The method comprises the steps that after an initial registration password submitted by a user is received, lightweight hash is calculated; performing weak password mark hit matching, and outputting a password state matching result; if not, parallel feature vectors are extracted through an SIMD instruction set; loading to a multi-strategy fusion model, carrying out multi-strategy password strength characteristic fusion evaluation, and outputting a real-time password strength label; matching an asynchronous scene, performing asynchronous dual-thread application scene risk detection, and outputting a heterogeneous scene risk report; randomly disturbing the initial registration password to obtain a temporary standby password library; and loading to a registration interface for visual display. The technical problems that in the prior art, password evaluation depends on a model with the large calculation amount, the evaluation speed is low, real-time password detection cannot be achieved, and then user experience and system efficiency are affected are solved.

The invention provides a context-based deep mail password strength measurement method, which comprises the following steps of: introducing user context information such as an e-mail, a name and a birthday on a basic password measurement model framework, and realizing information fusion through a multi-head self-attention mechanism; and a password sequence probability calculation model is constructed in combination with a character-level long-short-term memory network (LSTM). An evaluation system taking guess times as a core index is established to quantify the performance difference of different models under the condition that whether user context information exists or not. Experiments show that the method can more truly reflect the cracking capability of an attacker when the attacker masters the context information of the user.

The invention provides a weak password detection method based on multi-modal feature fusion and dynamic behavior analysis. According to the method, multi-dimensional feature extraction is innovatively introduced, including password entropy, semantic relevance, user historical behaviors, system login frequency and the like, so that user feature adaptation is improved, and dependency on a static dictionary is reduced; in addition, through real-time interactive feedback, instant pushing of password strength evaluation and safety suggestions can be realized. Therefore, by means of the method, the problems that in an existing weak password detection technology, the static dictionary dependency is high, the user feature adaptation is insufficient, and real-time feedback is lacked can be solved, the weak password detection precision and defense efficiency of colleges and universities are remarkably improved, and an efficient and easy-to-deploy password security solution is provided for the education industry.

The invention relates to a weak password identification method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a large batch of structured query language data, and segmenting the large batch of structured query language data into a plurality of single structured query statements; determining a statement type to which each structured query statement belongs; extracting password information from the structured query statement of which the statement type is a target type, wherein the target type represents a statement type related to a database account password; and verifying the password strength of the password information to obtain a weak password identification result corresponding to the password information. By the adoption of the method, batch processing of the structured query statements can be achieved by segmenting a large batch of data, the objects needing weak password recognition are screened through the statement types, and therefore the weak password recognition efficiency is greatly improved.

The invention relates to the technical field of embedded system network security, and provides a relay protection embedded security gateway device, which comprises a proxy server module for analyzing a downlink message to perform user login authentication, authority auditing and routing addressing, and performing auditing log recording and transparent forwarding on an uplink message, realizing one-to-many proxy communication based on the frame head addressing information; the authority auditing module is linked with the proxy server module and the auditing log module and is used for directly disconnecting the request which does not pass the authority verification; the audit log module is used for recording user operation events, permission change and system security events, supporting multi-format log storage and management and realizing log rolling recording and roll file exporting through a database; and the user management module is used for realizing full-life-cycle management of user identities and supporting password strength strategy configuration and a continuous wrong login locking mechanism. The method is suitable for network security protection of the power embedded device, and has the advantages of low invasiveness and high maintainability.

This invention discloses a PCFG password strength evaluation method incorporating Pinyin patterns. The steps include: 1) extracting Pinyin patterns from a benchmark dataset and generating corresponding rule sets; 2) sequentially selecting rules from the rule set according to probability and generating corresponding passwords based on the probability of the terminal symbols in the patterns contained in the rules; 3) determining whether the currently generated password matches the corresponding user's password. If not, proceeding to step 2) changing the terminal symbols corresponding to the pattern and generating the password again. If all terminal symbols in the patterns contained in the rule have been exhausted, changing the rule and continuing to generate passwords; 4) when the password matches the corresponding user's password, determining the password strength of the corresponding user's password based on the number of rule changes. This invention significantly improves the effectiveness of password strength evaluation for passwords containing Pinyin, providing a more scientific evaluation method for user password security.

The invention provides an intelligent network connection automobile password security detection system, which comprises a protocol intelligent analysis module used for unpacking a multi-level vehicle-mounted communication protocol, carrying out field type identification on the unpacked vehicle-mounted communication protocol, carrying out password feature library matching on the vehicle-mounted communication protocol subjected to field type identification, and carrying out password feature library matching on the vehicle-mounted communication protocol subjected to field type identification; identifying whether each field of the vehicle-mounted communication protocol has a risk; the dynamic fuzz test module is used for performing fuzz test on fields of the vehicle-mounted communication protocol with risks and analyzing a fuzz test result; and the compliance evaluation module is used for generating a risk detection report based on the protocol intelligent analysis module and the dynamic fuzzy test module and constructing a password strength scoring model, and the password strength scoring model is used for evaluating the security strength of the field key. According to the invention, comprehensive assessment of the password security of the intelligent networked automobile is realized, and the risk detection report is generated according to all identified risks.

The invention discloses a password strength evaluation method based on self-labeling and integrated text classification. The method comprises the following steps: training a password guessing model; performing password intensity self-labeling, performing simulation attack based on the password guessing model obtained through S1 training, and completing password intensity value labeling according to the number of times of simulation attack; and carrying out password strength evaluation based on integrated classification, carrying out stacked integrated text classification learning on the data set marked with the password strength, and finally carrying out automatic evaluation on the password strength by utilizing a text classification model to obtain a password strength value. According to the method, the password intensity of the to-be-learned password data set is automatically labeled by using the password guessing attack method, so that the problems of large workload and strong subjective difference of manual data labeling are solved. According to the password strength evaluation method based on stacked ensemble learning, different password strength evaluators based on classification are integrated to mutually take the advantages, so that higher password strength evaluation accuracy is achieved.

The application discloses a power utilization information acquisition terminal with multi-layer security isolation and relates to the technical field of power utilization information acquisition. The terminal comprises the following steps: power line carrier, micro-power wireless, cellular and Ethernet are used to bear acquisition indexes, and evidence packages containing link fingerprint summaries, health scores and interference categories are generated; a security chip is used to issue a token, and the link fingerprint summaries, object permission gears and minimum password strength thresholds are bound; a security channel is first built on a backup bearing, and the consistency of fingerprints, the validity of tokens and the non-downgrade are checked, and double-bearing consistency is performed on high-risk writing; the link fingerprint summaries and sequence check roots in the token are used to unlock object gates, and evidence object driving minimum access control and parameter setting are periodically uploaded; the method improves copy stability, reduces switching delay, avoids downgrade and miswriting, and is more convenient for operation and maintenance supervision and network acceptance.

The invention discloses a WiFi password strength verification method and device, and the method comprises the steps: capturing a WiFi handshake packet, extracting a password hash value in the WiFi handshake packet, and comparing the password hash value with a predefined password strength library, thereby evaluating the WiFi password strength and generating a safety report. The method does not need to obtain the plaintext password of the WiFi of the user, guarantees the privacy of the user, has the characteristics of high efficiency, comprehensiveness and user friendliness, and is suitable for units and individuals with high information security requirements.

An information processing apparatus includes a user interface. The apparatus displays a software keyboard for inputting a password, using the user interface; in a case where a password strength meter indicating a strength of a password is set to be displayed using the user interface, calculates a strength of a password input from the software keyboard; and displays the software keyboard and the password strength meter indicating the strength of the input password, and in a case where a password strength meter indicating a strength of a password is set not to be displayed using the user interface, displays the software keyboard. In the case where a password strength meter indicating a strength of a password is set not to be displayed using the user interface, the password strength meter is not displayed.

The application discloses a password strength measurement method based on reinforcement learning, which comprises the following steps: firstly, constructing a password data set, then establishing a reinforcement learning model and a scoring model, training the reinforcement learning model and the scoring model, and obtaining an optimal reinforcement learning model; after the deployment is completed, a user inputs a password into the optimal reinforcement learning model, and outputs a probability; then the probability is compared with a password probability dictionary through a Monte Carlo calculation algorithm to obtain a guessing number of the password; and finally, according to the corresponding relationship between the guessing number of the password and the password strength, the password strength of the password is obtained. The password modeling method based on reinforcement learning regards the process of generating a password by a user as a Markov decision process, calculates the reward brought by each action, and can better model a password sequence; the application can resist online directional guessing attacks and offline wandering guessing attacks at the same time, and is more accurate and more robust.

This application provides a password verification method, device, storage medium, and program product, relating to the field of big data. The method includes: obtaining a user password to be verified; determining the target complexity level that the user password must meet; performing corresponding password security verification according to the target complexity level; performing a first verification on the user password when the target complexity level is first; performing both the first and second verifications on the user password when the target complexity level is second; and performing the first, second, and third verifications on the user password when the target complexity level is third; if all verifications of the user password pass, then the user password is allowed to be used. This method adds a verification dimension based on character space distribution, improving the accuracy of password strength assessment in complex business scenarios.

The present invention discloses a password security assessment method, device, electronic device, and storage medium based on a probabilistic inference model. The method includes obtaining user password information and user personal information; processing the user personal information according to preset PII tag setting rules to obtain multiple user PII tags; identifying and matching the user password information based on the multiple user PII tags to determine the multiple user PII tags; obtaining the uppercase and lowercase English character combination types in the user password information; matching the multiple user PII tags and the uppercase and lowercase English character combination types with a preset probability tree to determine the corresponding feature probabilities; calculating the probability of guessing the user password information based on the feature probabilities; and calculating the number of guesses for the user password information based on the guess probabilities; and determining the password strength level of the user password information based on the number of guesses for the user password information. The present invention can achieve a more accurate assessment of password security.

The invention discloses a dynamic password strength evaluation method for Internet of Things equipment, and relates to the technical field of Internet of Things security, and the method comprises the steps: obtaining a to-be-evaluated target password, carrying out the analysis of the target password, and extracting the basic characteristics of the password; generating initial password strength of the target password based on the password basic characteristics; mapping the initial password strength into attack cost according to context information of equipment corresponding to the target password; obtaining dynamic risk state data in the operation process of the equipment, and dynamically correcting the attack cost to obtain a dynamic password strength evaluation result of the target password; according to the method, probabilistic attack modeling is introduced, and equipment context and dynamic risk correction are combined, so that the problems that existing password strength evaluation is static and is separated from an actual attack environment of the Internet of Things are solved.

The invention discloses a password strength evaluation method and system based on industrial Internet of Things edge nodes, relates to the field of Internet of Things security, is applied to a node management gateway, and comprises the following steps: matching a plurality of edge nodes according to current service scene information; inputting the plurality of edge nodes into a preset node association knowledge graph for association clustering to obtain an association node graph of the plurality of edge nodes; calculating statistical parameters of the plurality of edge nodes based on the association node graph of the plurality of edge nodes; calculating risk propagation coefficients of the plurality of edge nodes according to the statistical parameters of the plurality of edge nodes; and according to the risk propagation coefficients of the plurality of edge nodes, correcting the password intensities of the plurality of edge nodes to obtain the corrected password intensities of the plurality of edge nodes, thereby solving the problem of insufficient edge node password intensity evaluation precision in the industrial Internet of Things at present.

Systems and methods provide context-aware password strength evaluation. In an embodiment, a method includes receiving a user password, wherein the user password is associated with at least one of a newly created password, an updated password, or an existing password to be analyzed; parsing the user password into one or more segments; determining, for each segment, discoverability measures relative to personal information associated with the user, wherein the personal information includes at least one of publicly available data or non-public data; calculating a context-aware password strength rating based on the discoverability measures of the one or more segments; and providing feedback to the user regarding the context-aware password strength rating.

In an example embodiment, an efficient, automated method to generate password guesses is provided by leveraging online text sources along with natural language processing techniques. Specifically, semantic structures in passwords are exploited to aid system in generating better guesses. This not only helps cover instances where traditional password meters would indicate a password is safe when it is not, but also makes the solution robust against fast-evolving domains such as new slang in natural languages or new vocabulary arising from new products, product updates, and services.

The application provides a weak password detection method based on multi-modal feature fusion and dynamic behavior analysis. The method innovatively introduces multi-dimensional feature extraction, including password entropy, semantic correlation, user historical behavior, system login frequency, etc., to improve user feature adaptation and reduce dependence on static dictionaries. In addition, through real-time interactive feedback, password strength assessment and security recommendations can be pushed in real time. Therefore, the method of the application can solve the problems of strong dependence on static dictionaries, insufficient user feature adaptation, and lack of real-time feedback in existing weak password detection techniques, significantly improving the accuracy and defense efficiency of weak password detection in colleges and universities, and providing an efficient and easy-to-deploy password security solution for the education industry.

The invention discloses an electricity utilization information acquisition terminal with multilayer security isolation, which relates to the technical field of electricity utilization information acquisition, and comprises the following steps of: bearing acquisition indexes on power line carrier, micropower wireless, cellular and Ethernet, and generating an evidence packet containing a link fingerprint abstract, a health score and an interference category; issuing an undertaking token by the security chip, and binding the link fingerprint abstract, the object permission level and the minimum password strength threshold; establishing a secure channel in a standby bearer, verifying that fingerprints are consistent and tokens are effective and do not degrade, and executing dual-bearer consistency for high-risk writing; unlocking an object gate through double certification of a link fingerprint abstract and a sequence check root in the token, and periodically uploading an evidence object to drive minimum access control and parameter setting; according to the method, the reading stability is improved, the switching time delay is reduced, degradation and miswriting are avoided, and operation and maintenance supervision and network access acceptance are more convenient.

The invention discloses a password security assessment method and device based on a probability inference model, electronic equipment and a storage medium. The method comprises the following steps: acquiring user password information and user personal information; processing the personal information of the user according to a preset PII tag setting rule to obtain a plurality of user PII tags, and identifying and matching the password information of the user based on the plurality of user PII tags to determine the plurality of user PII tags; obtaining a capital and small case combination type of English characters in the password information of the user; matching the plurality of user PII tags and the English character capital and small case combination types with a preset probability tree, and determining respective corresponding feature probabilities; calculating the guess probability of the password information of the user according to the feature probability; calculating guessing times of the user password information according to the guessing probability; and determining the password strength level of the user password information according to the guess times of the user password information. According to the scheme, the password security can be evaluated more accurately.

The application discloses a key recovery method and system based on password strength distribution and threshold combination, relates to the password management and cryptography field, and comprises four stages of initialization, recovery password registration, recovery password revocation and key recovery. The initialization stage constructs secret sharing public parameters and a recovery bucket storage structure. In the registration stage, a candidate recovery password is assigned with a corresponding number of real shares according to the strength of the candidate recovery password, random data is filled to form fixed-length recovery data, and the recovery data is stored in a corresponding recovery bucket in an encrypted manner. In the revocation stage, the recovery permission of a specified recovery password can be cleared, and the storage state is synchronously updated. When a user forgets a master password, an effective share is extracted by inputting a registered recovery password, and the password library key is reconstructed after the cumulative threshold is reached, so that the password library access permission is recovered. The application does not require the user to additionally remember a special recovery password, considers the recovery availability and the cryptographic security, and has good cloud observation resistance.

The present disclosure provides a password strength evaluation method and device, and a server. The method comprises: obtaining a password sample set, the password sample set comprising a plurality of password sample sets, each password sample set comprising a plurality of password samples having the same attribute characteristics; encoding each password sample in each password sample set to generate a plurality of word segmentation vectors; generating a feature vector for each password sample using the plurality of word segmentation vectors; generating a feature vector generator based on the feature vectors of the plurality of password samples; determining the password strength of a password to be evaluated based on the plurality of feature vector generators corresponding to the plurality of password sample sets, and outputting an evaluation result.

This invention belongs to the field of cryptographic strength detection, and particularly relates to an intelligent cryptographic strength detection system and method based on an optimized exhaustive algorithm. The system includes a receiving module, an analysis module, a risk assessment module, and a strength generation module. It optimizes traditional exhaustive traversal through probabilistic guided brute-force attack simulation analysis, combines multi-source implicit weak password feature extraction, and dynamically fuses the weights of the two analysis results using real-time attack data to generate a dynamic comprehensive risk value. Simultaneously, the system performs real-time comparisons using a centralized weak password dictionary database and can automatically trigger asynchronous batch traceability detection of historical passwords after dictionary updates. Finally, the system integrates the dynamic risk value and dictionary assessment results to output an accurate strength level and risk report. This invention effectively overcomes the problems of low traversal efficiency, dimensionality explosion, and difficulty in tracing historical passwords in traditional methods, significantly improving the real-time performance, accuracy, and scenario adaptability of the detection.

The application provides a multi-strategy fusion password detection method and system and a medium, and relates to the technical field of data processing.The method comprises the following steps: after receiving an initial registration password submitted by a user, calculating a lightweight hash; performing weak password label hit matching and outputting a password state matching result; if no hit is found, extracting a parallel feature vector through an SIMD instruction set; loading the parallel feature vector into a multi-strategy fusion model to perform multi-strategy password strength characteristic fusion evaluation and output a real-time password strength label; matching an asynchronous scene to perform asynchronous double-thread application scene risk detection and output a heterogeneous scene risk report; randomly disturbing the initial registration password to obtain a temporary backup password library; and loading the temporary backup password library into a registration interface for visual display.The application solves the technical problem that the prior art relies on a model with a large amount of calculation to perform password evaluation, which results in slow evaluation speed, cannot realize real-time password detection, and further affects user experience and system efficiency.

The application relates to the technical field of distributed machine learning and network security, in particular to a quantum-resistant federated learning framework and a training security processing method. The quantum-resistant federated learning framework comprises at least one server and at least one client corresponding to each server; and a federated training scheduling module, a post-quantum key encapsulation module, a post-quantum digital signature algorithm module, a symmetric encryption protection module and a security verification and aggregation module respectively arranged on each server and each client. The framework can integrate the post-quantum secure communication capability by extending the gRPC transmission layer of Flower, improve the message confidentiality, message integrity, identity authentication and the continuity, security and controllability of the multi-round training process of the federated learning system under the threat of quantum computing, and be suitable for distributed collaborative modeling scenes such as medical treatment, finance, government affairs and industrial internet which have high requirements for communication security and long-term password strength.

The present invention discloses a password control detection system and method for a host security management platform, and relates to the technical field of network host security. The technical solution comprises: a central processing unit, which is used to ensure the calculation and operation of the system; a target host discovery module, which is used to discover the network host for security management; a password collection module, which is used to collect the control password of the network host, and the password collection module comprises a system collection module, an application collection module and a database collection module. The beneficial effect of the present invention is that: an intelligent analysis module and a password arrangement module are designed, and when the intelligent analysis module analyzes that the password is a weak password, the password arrangement module can automatically re-arrange the control password of the network host. In this way, the system can automatically arrange a new password when detecting that the password is a weak password, thereby improving the password strength of the network host, thereby preventing the password from being cracked and the network host from being invaded.

The invention discloses a password complexity judgment method, which comprises the following steps of: S1, counting the number of character types contained in a password character string, and determining type complexity D; s2, carrying out statistics on a conversion condition between adjacent characters in the password character string, and calculating conversion complexity T according to the conversion condition; s3, calculating the basic complexity C of the password character string; s4, calculating length complexity S according to the length of the password character string; s5, the final complexity K is equal to (Dwd * Twt * Cwc * Sws) 1 / 13; in the formula, wd is the weight of D, wt is the weight of T, wc is the weight of C, and ws is the weight of S; s6, if the final complexity is smaller than the complexity threshold value, warning or prompting that the password strength is insufficient; if the final complexity is larger than or equal to the complexity threshold value, prompting is not carried out or the password intensity is prompted to be sufficient. According to the scheme, the character transformation condition is fully considered, and the judgment result is more rigorous.