9 results about "Deterministic finite automaton" patented technology

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.

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.

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 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 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.

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.

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.