3 results about "Sequence alignment algorithm" patented technology

This disclosure provides a security detection method, apparatus, and device for communication protocols, comprising: obtaining the structure of the communication protocol through unsupervised learning and structural parsing based on bidirectional raw traffic data; utilizing sequence alignment algorithms to find common patterns and variable fields among packets in different protocol session streams; identifying high-frequency byte sequences that consistently appear in application layer payload data; dividing the payload of a single packet into multiple fields and inferring the semantic type of each field; and constructing a protocol syntax tree for the communication protocol; then, based on the protocol syntax tree, modeling normal communication behavior to obtain a behavioral baseline of the behavioral patterns under normal communication behavior; and performing anomaly detection on real-time traffic obtained from the communication network based on the protocol syntax tree and the behavioral baseline. Thus, without prior knowledge of the detailed protocol specifications, it can intelligently learn from communication behavior to discover potential threats, reducing the application limitations of this security detection method.

The invention relates to the field of computer internet and cloud computing, and discloses a project dimension-based precise operation and maintenance quantification and intelligent recommendation method, which comprises the following steps of: encoding distributed link tracking data into an ordered service gene sequence, and realizing automatic identification and resource quantification of a project by using a sequence alignment algorithm. By extracting a gene mutation rate and an epigenetic modification tag, system stability and external environment constraint are dynamically sensed. On the basis, a non-cooperative game model containing performance, cost and risk agents is constructed, game rules are dynamically reconstructed based on gene characteristics, risk sensitivity and constraint strategy space are adjusted in a non-linear mode, a biological adaptability evolution mechanism is simulated, a horizontal gene transfer mechanism is introduced, and a cold start decision of a new project is optimized. And finally, an optimal operation and maintenance configuration instruction is generated by solving a Nash equilibrium point. According to the method, accurate quantification, dynamic self-adaption and risk control of operation and maintenance decisions in a complex cloud environment are effectively realized.

The invention discloses a fine-grained evaluation method for logic security of a large language model, which comprises the following steps of: aiming at an obtained dynamic test case, analyzing variable interaction influence, injecting a private instruction sequence by embedding a risk module, and determining a test case version of which the difficulty is adjusted; selecting an intermediate step sequence from the determined test case version, and calculating a deviation value with a standard reasoning path by adopting a sequence comparison algorithm to obtain a fine-grained deviation index set; according to the obtained deviation index set, the accuracy data derived in multiple steps are fused, if the deviation value exceeds a preset threshold value, the deviation value is marked as a logic bottleneck point, and a potential safety crash position is judged; quantifying a step-by-step reliability index of the reasoning process through the judged safety crash position to obtain a numerical score of the logic capability; and a safety performance subset is extracted from the obtained numerical score, clustering analysis is adopted to conclude a performance mode in a high-risk scene, and a final comprehensive evaluation report is determined.