mlsanityData to 13 Oct 2026

SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis

arXiv 2104.00764 ↗First posted 1 Apr 2021cs.CLcited by 4

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Abstract (arXiv)

Darknet market forums are frequently used to exchange illegal goods and services between parties who use encryption to conceal their identities. The Tor network is used to host these markets, which guarantees additional anonymization from IP and location tracking, making it challenging to link across malicious users using multiple accounts (sybils). Additionally, users migrate to new forums when one is closed, making it difficult to link users across multiple forums. We develop a novel stylometry-based multitask learning approach for natural language and interaction modeling using graph embeddings to construct low-dimensional representations of short episodes of user activity for authorship attribution. We provide a comprehensive evaluation of our methods across four different darknet forums demonstrating its efficacy over the state-of-the-art, with a lift of up to 2.5X on Mean Retrieval Rank and 2X on Recall@10.

Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Builds on 18 of its 50 references that are in the map. First posted on arXiv 1 Apr 2021.

Builds on

18 of 50 references.

References · 18

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6 more
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Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 1.

4 papers.

  1. 2022VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Webcited by 10
  2. 2022NBC-Softmax : Darkweb Author fingerprinting and migration trackingcited by 1
  3. 2023URM4DMU: an user represention model for darknet markets userscited by 0
  4. 2025Per-sender neural network classifiers for email authorship validationcited by 0