The obligation of network security management in the era of deep falsification: the legal, judicial and policy implications of artificial intelligence abuse.

The diffusion of deepfake technology has reshaped the structure of online risks and posed new institutional demands on existing network security management obligations. From a risk-oriented perspective, this article constructs a quantitative model for assessing artificial intelligence misuse risks a...

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Published in:Crime, Law & Social Change Vol. 84; no. 1; pp. 1 - 19
Main Authors: Guo, Kai, Qiu, Yaxian
Format: Article
Published: Springer Nature 7/14/2026
Subjects:
Online Access:View this record in EBSCOhost
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      dt: 7/14/2026
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        10.1007/s10611-026-10299-w
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        atl: The obligation of network security management in the era of deep falsification: the legal, judicial and policy implications of artificial intelligence abuse.
      aug:
        au:
          Guo, Kai
          Qiu, Yaxian
        affil:
          Department of Law, Shanxi Police College, National Security Key Areas Public Opinion Risk Research Center, 030401, Taiyuan, China
          Department of Criminal Investigation, Shanxi Police College, National Security Key Areas Public Opinion Risk Research Center, 030401, Taiyuan, China
      su:
        Government policy
        Legal judgments
        Artificial intelligence
        Legal liability
        Risk assessment
        Scientific method
        Computer network security
      sug:
        subj:
          Government policy
          Legal judgments
          Artificial intelligence
          Legal liability
          Risk assessment
          Scientific method
          Computer network security
      keyword:
        Artificial intelligence and the rule of law
        Deepfakes
        Network security management obligations
        Risk-oriented governance
        Artificial intelligence and the rule of law
        Deepfakes
        Network security management obligations
        Risk-oriented governance
      ab: The diffusion of deepfake technology has reshaped the structure of online risks and posed new institutional demands on existing network security management obligations. From a risk-oriented perspective, this article constructs a quantitative model for assessing artificial intelligence misuse risks and employs simulation-based experiments to systematically analyse governance outcomes under different levels of management obligations. The findings indicate that response timeliness, institutionalized procedures, and evidence preservation play a decisive role in damage mitigation, while reliance on technical detection alone is insufficient to achieve effective governance. The simulation model assesses the four types of governance systems for deepfake misuse across different scenarios through 10,000 iterations of the simulation experiment. Based on the experimental results, the article proposes a risk-tiered configuration of network security management obligations, providing empirical support for judicial determinations of the duty of reasonable care and for policy-level collaborative governance.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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