30 results about "Deterministic finite automaton" patented technology

An end-to-end rendering system enforces policy-constrained, symbolic presentation of artificial-intelligence (AI) outputs prior to any pixel emission. An AI accelerator emits inference tokens as (token identifier, confidence, domain tag) tuples into an output FIFO. A graphics processor with a command processor and SIMD co-processor executes a policy engine that runs a deterministic finite automaton (DFA) stored in non-transitory memory. The DFA consumes the tuples and produces, before any frame-buffer writes, a permit / deny decision and a visibility mask that constrain presentation attributes. A glyph selector maps permitted tuples to entries in a constrained glyph dictionary specifying a glyph identifier, semantic class, and allowed substitutions. A provenance tagger computes a cryptographic hash over at least the glyph identifier, a DFA-state policy identifier, a session nonce, and a checksum of the tuples to create an evidence capsule bound to the glyph. A device-aware renderer, consulting a device profile registry and a rendering grammar, emits a renderable asset for the glyph only when permitted by the visibility mask and grammar. A justification ledger records, for each displayed glyph, the evidence capsule and a monotonic timestamp. Executed entirely within the graphics processor, the pipeline prevents unauthorized tokens from entering the display path, enables cryptographically verifiable traceability of visible content, and reduces bandwidth by representing outputs as glyph identifiers rather than text or raster imagery, while allowing runtime policy updates without modifying the underlying inference model.

The invention discloses a sandbox type trusted data space construction method and equipment based on a trusted verification architecture, belongs to the technical field of data security circulation and trusted computing, and aims to overcome the defects that a traditional sandbox behavior is unknowable and untrusted and a strategy is rigid. The method comprises the following steps of: starting a sandbox in a hardware trusted execution environment and generating a task unique context identifier; intercepting system call by a monitoring agent; generating a chained operation certificate containing preorder certificate hash; compiling an advanced security policy into a deterministic finite automaton executable policy set; and the auditing unit is used for generating a decision instruction in an illegal scale, storing the chain anchor point to the non-tampering system, forcibly executing decision and generating a Merkel tree evidence. The equipment correspondingly comprises a sandbox management module, a behavior monitoring module, a strategy compiling module, a verification judgment module and an auditing execution module. The full-flow transparent tracing of the operation in the sandbox is realized, the strategy dynamic adaptation is supported, and the problem that a traditional sandbox monitoring log is easy to counterfeit and difficult to verify is solved.

The invention relates to the technical field of computer data processing and network security, in particular to an illegal character automatic cleaning system, which comprises a rule compiling module for monitoring rule change, performing semantic fusion and topological mapping on a rule set, constructing a deterministic finite automaton and mapping the deterministic finite automaton into a state transition table; the state switching module is used for constructing a double-buffer context and operating lock-free switching through an atomic pointer to realize hot updating; the speculation execution module is used for carrying out vectorization pre-scanning based on a state transition table by utilizing single-instruction multi-data stream parallel loading, identifying a walk path, falling into a safe state for releasing and falling into a trap state for triggering external verification; the self-adaptive feedback module is used for counting trap state triggering frequency, generating a rule allergy report and dynamically adjusting the size of a read fragment; according to the method, the contradiction between rule flexibility and execution efficiency is solved, and high-performance cleaning based on speculative execution is realized.

A text segmentation and sensitive word detection method based on matrix multiplication, comprising the following steps: obtaining an original text string and a sensitive word library; constructing a deterministic finite state automaton tree diagram of sensitive words according to the sensitive word library; converting the original text string into a text character two-dimensional matrix and recording the length of the text character two-dimensional matrix; constructing a matching two-dimensional matrix according to a horizontal matching rule, a vertical matching rule, an oblique matching rule and an inverse oblique matching rule, the length of the matching two-dimensional matrix being the same as that of the text character two-dimensional matrix; performing dot multiplication processing on the text character two-dimensional matrix and the matching two-dimensional matrix to obtain a corresponding result matrix; generating a corresponding matching text string according to the result matrix, and matching with the deterministic finite state automaton tree diagram to determine whether there is a sensitive word. The application supports interval text character information detection, improves the sensitive word detection accuracy and detection efficiency.

Systems and methods for implementing fall-through slots for deterministic finite automatons (DFAs) in a regular expression (regex) accelerator are provided. A method includes compiling a set of regular expression patterns to generate an output file, wherein the output file comprises information related to a deterministic finite automaton (DFA) graph, including fall-through information indicative of whether a transition associated with any nodes of the DFA graph comprises a fall-through transition. The method further includes during processing of a payload, executing transitions associated with the DFA graph, including any fall-through transitions.

A curiosity-driven Android app automatic testing method includes the following steps:1) a left part represents a pre-processing assembly which achieves abstraction of an Android app state based on an Android interface structure; 2) a right part is curiosity-driven reinforcement learning module which maintains a historical access state set and optimizes an exploration policy constantly to guide a test to find more new states under the guidance of a reward function based on a curiosity thought; and 3) a middle part represents an advanced guidance module of a deterministic finite automaton (DFA), where the DFA is constructed during operation to record all access states and frequencies thereof; and if the new states are not explored within a given time budget, an AndroidExplore selects the most curious state as a starting point of a next exploration according to global information of the DFA.

An embodiment of this specification provides a method, apparatus, storage medium, and device for constructing a regular expression engine. The method includes: traversing each character of a regular expression, and marking consecutive ordinary characters in the regular expression as a consecutive string; constructing an initial non-deterministic finite automaton based on the regular expression, where the NFA state transition relationships corresponding to the characters marked as the consecutive string are merged into the same NFA state transition relationship. When constructing an NFA, in the embodiment of this specification, by merging the transition relationships corresponding to consecutive ordinary characters marked as a consecutive string into the same transition relationship, the number of unnecessary states and the number of transition relationships are reduced. Therefore, compared with the existing NFA construction methods, the NFA constructed by the method in the embodiment of this specification has higher execution efficiency, and the computing resources consumed during its construction are also relatively low.

The present invention provides a novel explicit analytical mathematical modeling method for hybrid automata systems. First, the switching mode of a continuous-time switched system model with differential form is transformed into a constant switching signal that depends on an index at the switching moment. Then, the discrete state nodes and discrete input events in the logical evolution graph of a deterministic finite automaton are represented by their own logical vector forms respectively. In addition, by using the semi-tensor product tool of matrix calculation, an algebraic characterization form of the dynamics of the switching signal based on the automaton is given, that is, a restricted automaton-dependent switching mechanism based on the evolution mode of a deterministic finite automaton is designed. Finally, by organically integrating a continuous switched system and a discrete deterministic finite automaton, an explicit mathematical model of a hybrid automaton with a hybrid form is given. The model constructed by the present invention can directly represent and describe the hybrid characteristic problems related to discrete event-driven and continuous dynamic processes in the fields of computers and control.

This application discloses a method, apparatus, device, and storage medium for compressing a deterministic finite automaton. The method includes the following steps: reading characteristic characters from a characteristic string set; constructing a deterministic finite automaton based on the characteristic characters; compressing the deterministic finite automaton based on the failure paths and default paths of the state of the deterministic finite automaton to obtain a TCAM table; and using the TCAM table for string matching. This application compresses the TCAM using the failure paths and default paths of the state of the deterministic finite automaton, eliminating the need to compress the TCAM using a common suffix tree. The state encoding length is not restricted by the string, thereby improving the compression ratio of the DFA.

The invention provides a dynamic rule updating method and a dynamic rule updating system, and relates to the field of financial science and technology or other related fields. The method comprises the steps of monitoring whether a matching rule corresponding to a job is updated or not when the job runs; if it is monitored that the matching rule is updated, obtaining an updated target matching rule, and compiling a new non-deterministic finite automaton based on the target matching rule; a target event sequence matched with the target matching rule is obtained, the target event sequence is input into a new non-deterministic finite automaton, and the non-deterministic finite automaton is used for being converted into a termination state when the target event sequence meets the target matching rule; and when it is detected that the new non-deterministic finite automaton is in the termination state, triggering a preset action. According to the method provided by the invention, the rule dynamic updating of the Flink CEP can be realized, the cross-node communication overhead and rule synchronization delay in the rule updating process can be eliminated, and the rule updating failure risk caused by the monitoring node fault can be avoided.

This invention relates to the field of robot motion planning and formalization technology, and discloses a method and system for reactive motion planning of robots. The method includes: establishing a set of atomic propositions and a shared-safe linear temporal logic task reduction based on the task to be performed by the robot; converting the task reduction into a deterministic finite automaton, constructing a convex region in the robot configuration space, and establishing a convex set state transition system; constructing a convex set graph by multiplying the convex set state transition system with the deterministic finite automaton, and solving for the initial trajectory; performing structured relaxation on the deterministic finite automaton; and reconstructing the convex set graph based on the relaxed deterministic finite automaton, starting from the current robot configuration, and solving for the replanned trajectory. This invention achieves safe, verifiable, and highly robust execution of long-term sequential tasks of robots in dynamic environments by unifying task semantic hierarchy, automaton logic relaxation, and continuous trajectory optimization of the convex set graph.

The invention relates to a patient nursing guiding method and device, electronic equipment and a storage medium, and the method comprises the steps: constructing a determined finite state automaton which comprises a state set, an input coincidence set, a transfer function, an initial state and a receiving state set, and detecting the current state of a patient in real time based on the determined finite state automaton, and based on the current state of the patient, obtaining multi-dimensional nursing information matched with the current state by utilizing a retrieval enhancement generation algorithm, and based on the multi-dimensional nursing information, generating a nursing suggestion through a preset cue word template so as to perform nursing guidance on the patient through the nursing suggestion. Compared with the prior art, the treatment compliance and the self-management ability of the patient can be improved, the healthy behavior of the patient is promoted, the fear degree of the patient is reduced, the anxiety psychological state of the patient is relieved, the out-of-hospital treatment effect of the patient is improved, the continuity and the high efficiency of medical service are powerfully promoted, and better and more comprehensive medical support is provided for the patient.

The embodiment of the invention provides a segmentation acceleration method and device for determining a finite state automaton, equipment and a medium, an engineering segmentation problem is converted into a computable and optimizable graph theory source set problem, a continuous code adaptive to an SIMD instruction is created for each segment, and intra-segment transfer and inter-segment routing are managed through a double-table structure, so that the segmentation acceleration speed of the finite state automaton is improved. And finally, seamless segment switching is realized through a state checking mechanism during operation. According to the method, the hardware limitation of the existing SIMD instructions such as PSOFB on the DFA state number is broken through, so that the large-scale DFA can still be accelerated by using the hardware instructions after being segmented, the application range is expanded, meanwhile, the high-speed processing capacity is kept through the structural design, and the target of exponentially expanding the limitation of the existing acceleration method on the DFA state number is achieved.

The application provides a ship energy efficiency complex task automatic processing method and system based on a large language model, a storage medium and equipment, wherein the ship energy efficiency knowledge set is divided and coded, and the pre-training of the ship energy efficiency large model is carried out based on a general large language model base; the ship energy efficiency tool set and the general tool set are constructed, and the ship energy efficiency large model is given professional field data processing capability; the intention analysis module is used to fully understand and analyze the user intention, and the formatted output of the user intention is formed; the task automatic planning non-deterministic finite automaton is constructed; and the user command understanding and tool calling are carried out based on the task automatic planning result and the trained ship energy efficiency large model, and the execution result is generated. The technical scheme of the application can reduce the illusion output, tool calling and complex task processing failure probability, help the ship reduce energy consumption, reduce carbon emission and improve operation efficiency, further improve the digitalization level of the ship energy efficiency, and improve the data and knowledge utilization rate.

The application provides a geographic coordinate optimization method based on a road constraint multi-source network geographic coding platform, belongs to the technical field of geographic coding result data processing, and comprises the following steps: S1, inputting a text address into each geographic coding platform to obtain coding results converted into a unified coordinate system; S2, making a circle with each coding result as a center, extracting a candidate road segment set in the circle, and determining a road name to which the coding result belongs by calculating an Euclidean distance; S3, acquiring a road name by performing word segmentation on the text address based on a regular expression of a non-deterministic finite automaton (NFA) and a backtracking mechanism; and S4, performing semantic consistency comparison on the road name obtained in S2 and the word segmentation result in S3, and determining a final coding result according to the number of successful comparisons. The method can improve the accuracy of the coding result.

Systems and methods for implementing range slots for deterministic finite automatons (DFAs) in a regular expression (regex) accelerator are provided. A method includes compiling a set of regular expression patterns to generate an output file, where the output file comprises information concerning a deterministic finite automaton (DFA) graph, including range information indicative of whether any of a set of transitions along an edge associated with the DFA graph can be captured by a respective single transition. The method further includes during processing of a payload, based on the range information, executing the respective single transition along the edge associated with the DFA graph.

Techniques for data pattern analysis using deterministic finite automaton are described herein. In one embodiment, a number of transitions from a current node to one or more subsequent nodes representing one or more sequences of data patterns is determined, where each of the current node and subsequent nodes is associated with a deterministic finite automaton (DFA) state. A data structure is dynamically allocated for each of the subsequent nodes for storing information associated with each of the subsequent nodes, where data structures for the subsequent nodes are allocated in an array maintained by a data structure corresponding to the current node if the number of transitions is greater than a predetermined threshold. Other methods and apparatuses are also described.

Computer-implemented systems and methods are detailed for establishing information on states of a machine-executable contract on a blockchain, for instance in the context of unspent transaction outputs (UTXOs) and the determination of states within deterministic finite automaton (DFA) implementations of contracts. The states are determined using agent public keys, each public key having metadata for information of interest associated with codes or tags. Each of the agents provides a respective public key into a multi-signature redeem script that generates a locking script, with a hash to which a scriptPubkey is designated. ScriptPubKey values of each script may be used to provide keys for use in constructing an external database and mapping the keys from the scriptPubKey values. Upon searching the blockchain, the database is used to determine if the information of interest is present in UTXOs. A match from the search indicates, in a definitive manner, the state.

Systems and methods for adaptive backtracking depth limit for non-deterministic finite automaton implementations are provided. A method includes, as part of a match attempt between a regular expression (regex) pattern and a payload, a non-deterministic finite automaton (NFA) instance executing instructions for an NFA graph having a plurality of nodes linked via arcs indicative of transitions among states of the NFA instance. The method further includes during execution of the instructions for the NFA graph, using a backtrack-depth counter counting a number of times a current state of the NFA graph has been previously visited during the match attempt between the regex pattern and the payload. The method further includes, upon the backtrack-depth counter for the NFA instance reaching or exceeding an adaptive backtracking depth limit for the NFA instance, terminating the match attempt between the regex pattern and the payload.

The present application relates to computer data processing and network security technical field, specifically to a kind of illegal character automatic cleaning system, comprising: rule compiling module: monitoring rule changes, rule set is fused with topological mapping with semantics, constructs deterministic finite automaton and is mapped into state transition table;State switching module: constructs double-buffer context, realizes hot update by atomic pointer operation lockless switching;Speculative execution module: utilize single-instruction multiple-data stream parallel loading, vectorized pre-scanning is carried out based on state transition table, identifies wandering path, falls into safe state and releases, falls into trap state and triggers external check;Adaptive feedback module: the frequency of trap state triggering is counted, generates rule hypersensitivity report, dynamically adjusts reading fragment size;The present application solves the contradiction between rule flexibility and execution efficiency, realizes high-performance cleaning based on speculative execution.

According to the present specification, a method for inspecting a high-speed network packet payload by a terminal includes: a step of receiving L7 (Layer 7) policy related to containers from a user; a step of extracting string patterns to be inspected for each of the containers on the basis of the L7 policy through a pattern compiler; a step of creating a deterministic finite automaton (DFA) on the basis of the extracted string patterns through the pattern complier; and a step of converting a state transition table of the deterministic finite automaton into a match-action table through the pattern compiler and storing the match-action table in an eBPF (extended Berkeley Packet Filter) map for a payload inspection engine.

Systems, methods, and computer-readable medium for splitting regular expressions between non-deterministic finite automaton and deterministic finite automaton are provided. A method includes parsing a set of regular expression patterns to generate an output. The method further includes processing the output to determine whether any of the set of regular expression patterns meets a specified criteria including whether a regular expression pattern is a single path regular expression. The method further includes using a first splitting process, splitting any of the set of regular expression patterns that meet the specified criteria into a first set of tokens. The method further includes using a second splitting process, different from the first splitting process, splitting any of the set of regular expression patterns that fail to meet the specified criteria into a second set of tokens.

Systems and methods for adaptive backtracking depth limit for non-deterministic finite automaton implementations are provided. A method includes, as part of a match attempt between a regular expression (regex) pattern and a payload, a non-deterministic finite automaton (NFA) instance executing instructions for an NFA graph having a plurality of nodes linked via arcs indicative of transitions among states of the NFA instance. The method further includes during execution of the instructions for the NFA graph, using a backtrack-depth counter counting a number of times a current state of the NFA graph has been previously visited during the match attempt between the regex pattern and the payload. The method further includes, upon the backtrack-depth counter for the NFA instance reaching or exceeding an adaptive backtracking depth limit for the NFA instance, terminating the match attempt between the regex pattern and the payload.

Systems and methods for implementing range slots for deterministic finite automatons (DFAs) in a regular expression (regex) accelerator are provided. A method includes compiling a set of regular expression patterns to generate an output file, where the output file comprises information concerning a deterministic finite automaton (DFA) graph, including range information indicative of whether any of a set of transitions along an edge associated with the DFA graph can be captured by a respective single transition. The method further includes during processing of a payload, based on the range information, executing the respective single transition along the edge associated with the DFA graph.

Systems and methods for implementing fall-through slots for deterministic finite automatons (DFAs) in a regular expression (regex) accelerator are provided. A method includes compiling a set of regular expression patterns to generate an output file, wherein the output file comprises information related to a deterministic finite automaton (DFA) graph, including fall-through information indicative of whether a transition associated with any nodes of the DFA graph comprises a fall-through transition. The method further includes during processing of a payload, executing transitions associated with the DFA graph, including any fall-through transitions.

Systems, methods, and computer-readable medium for splitting regular expressions between non-deterministic finite automaton and deterministic finite automaton are provided. A method includes parsing a set of regular expression patterns to generate an output. The method further includes processing the output to determine whether any of the set of regular expression patterns meets a specified criteria including whether a regular expression pattern is a single path regular expression. The method further includes using a first splitting process, splitting any of the set of regular expression patterns that meet the specified criteria into a first set of tokens. The method further includes using a second splitting process, different from the first splitting process, splitting any of the set of regular expression patterns that fail to meet the specified criteria into a second set of tokens.

The invention relates to the technical field of heterogeneous graph regular path query, in particular to a heterogeneous graph regular path query method, system and device based on a Product graph and a medium, and the method comprises the steps that network data to be queried is modeled into a heterogeneous graph, and top points and sides are provided with type labels; defining a path query regular expression according to a query demand, and converting the regular expression into a deterministic finite automaton; dynamically constructing a product graph based on the heterogeneous graph and the deterministic finite automaton; and performing path search on the product graph to match a path conforming to the target path mode, and outputting path information. The method has the advantages that complex regular path query containing Kleene star number and other operators can be efficiently and accurately supported on the premise of not depending on pre-calculation indexes, meanwhile, real-time pruning is carried out through DFA state transition, and the efficiency and expression ability of path query in a large-scale dynamic heterogeneous graph are remarkably improved.

To provide a method and a system for performing, controlling, and automating tasks or processes on a block chain, such as, but not limited to, the Bitcoin block chain.SOLUTION: A system for providing the implementation of a process as an abstract DFA embodied on a computing platform-block chain including hardware and software components, has computing agents 3 that can interact with other entities 4 (for example, humans or other computers) to receive instructions. The instructions indicate which smart contract to create and execute. The computing agents 3 interact with the physical world to respond to and cause events in the outside of themselves (the real world).SELECTED DRAWING: Figure 1

The application provides an alarm data classification processing method and device for low-frequency high-risk attack alarm identification, which comprises the following steps: determining the importance of each alarm set based on attack frequency and alarm danger level, cyclically traversing the first attack service attribute of each alarm set in the attack set to obtain a target alarm set with the highest importance, and taking the first attack service attribute of the target alarm set as the second attack service attribute of the attack set; performing incremental sorting on the attack set with the same source IP address and destination IP address according to the start time attribute to obtain an attack sequence; sorting the target attack subsequence with a length greater than a preset length in the attack sequence according to the attack stage attribute and the second attack service attribute of the intrusion alarm to obtain a target attack subsequence; and performing classification processing on the target attack subsequence by using a suffix-based probabilistic deterministic finite automaton to obtain the importance of different attack sets, thereby improving the accuracy and reliability of attack identification.

The invention relates to a speech recognition and sensitive word detection method. The method comprises the following steps: collecting a speech signal, and carrying out preprocessing and acoustic feature extraction; constructing a speech recognition model, and generating corresponding text data based on the acoustic features; constructing a sensitive lexicon and constructing the sensitive lexicon into a finite automaton state diagram; traversing the text data, and detecting sensitive words according to the determined finite automaton state diagram; according to the method, in a voice environment containing noise, accent or homophone interference, the recognition accuracy of key terms in the field is effectively maintained, keyword recognition leakage and homophone replacement errors are reduced, and the subsequent detection reliability is improved from the source; and meanwhile, through a deterministic matching mechanism of the finite state automaton, the calculation overhead can be reduced, the matching jitter can be reduced, and a more stable hit position and a more stable context fragment can be output.