暗网加密流量分类与溯源技术研究综述OA

Anonymous network communication protocols have emerged as key technologies for protecting the anonymity of communication entities and data privacy.With the evolution of protocol architectures and the iterative upgrades of hidden service technologies,the Darknet ecosystem based on anonymous communica-tion has transformed into a platform for cybercrime.Among these,the Onion Routing protocol(Tor proto-col)has become the mainstream Darknet communication architecture due to its complex anonymity protection mechanisms.Within the Darknet,various criminal activities such as illegal transactions,data theft,and the sale of contraband primarily occur on hidden service websites and applications.From the perspective of cyber-security governance,identifying Darknet service traffic and tracing network entities holds significant theoreti-cal value and practical urgency.This paper systematically reviews research progress in the field of Darknet en-crypted traffic identification and tracing,focusing on three key dimensions:encrypted traffic feature recogni-tion,service application classification models,and encrypted traffic correlation analysis techniques.Through comparative analysis of the detection accuracy and applicability of different technical approaches,it reveals the existing technical bottlenecks in ciphertext parsing,behavioral pattern extraction,and deep correlation in-ference.