The invention discloses an anti-interference multi-
label webpage identification method and
system under an encrypted traffic condition, and the method comprises the steps: constructing a dynamic association graph through a
burst transmission structure of the encrypted traffic, precisely deconstructing
aliasing traffic through an entropy weight punishment mechanism and a node aggregation
algorithm, and outputting an independent substream sequence; extracting non-stationary time-frequency features for the substreams, fusing the non-stationary time-frequency features with graph topology features extracted based on a graph structure in a tangent space, generating disturbance samples by using an adversarial training environment, adjusting feature weights, and generating composite fingerprints; executing long
time sequence modeling on the Lie group manifold by using a Bi-Mama network, reserving a modulation interface, and outputting a preliminary recognition probability; and auditing causal consistency through a webpage loading
logic state machine, converting an abnormal state into geodesic line correction in a Lie algebra tangent space, and correcting network parameters on line through a reserved interface. According to the method, the problems that
aliasing traffic is difficult to deconstruct,
fingerprint robustness is insufficient and an identification result lacks logic consistency constraint are solved.