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posted by Fnord666 on Wednesday September 06 2017, @12:45AM   Printer-friendly
from the another-job-lost-to-automation dept.

Spotted on HackerNews is a link to a paper on Automated Crowdturfing Attacks and Defenses in Online Review Systems:

Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers. In this paper, we identify a new class of attacks that leverage deep learning language models (Recurrent Neural Networks or RNNs) to automate the generation of fake online reviews for products and services. Not only are these attacks cheap and therefore more scalable, but they can control rate of content output to eliminate the signature burstiness that makes crowdsourced campaigns easy to detect.

The paper, available from the arXiv link, contains the details of the attack which the paper notes "are largely indistinguishable from real reviews to human readers", and suggests defensive mechanisms based on "statistically detectable variations in the character-level distribution of machine-generated reviews".


Original Submission

 
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  • (Score: 2) by LoRdTAW on Wednesday September 06 2017, @01:32PM

    by LoRdTAW (3755) on Wednesday September 06 2017, @01:32PM (#564139) Journal

    It didn't fail. It was hijacked by the grass fuckers looking for more money followed by the government who are paid by said grass fuckers.

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