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Articles

Vol. 2 (2026)

Artificial Intelligence and Quantum Computing in Criminal Justice Systems: A Communication Engineering Perspective

DOI:
https://doi.org/10.31875/2979-1081.2026.02.01
Submitted
March 1, 2026
Published
2026-03-02

Abstract

Modern communication systems face unprecedented challenges in ensuring secure data transmission and real-time processing across distributed networks. The convergence of artificial intelligence (AI) and quantum computing (QC) fundamentally transforms communication engineering by introducing both enhanced capabilities for intelligent network management and critical threats to cryptographic security protocols that underpin global communications. These challenges are particularly acute in high-security domains such as criminal justice systems, where communication infrastructure must balance stringent security requirements with evidentiary reliability. The administration of criminal justice has historically relied on the epistemological reliability of evidence and the ontological security of information. However, the legal profession currently faces a radical discontinuity driven by the simultaneous maturation of Generative Artificial Intelligence (AI) and the accelerating development of Quantum Computing (QC). Generative AI has introduced a regime of "probabilistic truth," leading to the proliferation of hallucinated legal texts and synthetic media that threaten evidentiary standards. Parallel to this, the looming reality of QC poses a fundamental threat to the cryptographic locks securing sensitive criminal justice data, notably through strategies that target current encrypted data for future decryption. As the integration of these advanced technologies becomes an irreversible trend, there is a critical need to synthesize these divergent yet interconnected threats to understand their collective impact on judicial integrity. This review analyzes the epistemological crisis precipitated by the integration of algorithmic text generation into legal workflows and the challenges posed to digital forensics by the potential compromise of encryption standards. Furthermore, it explores the transformative potential of Quantum Machine Learning (QML) in unraveling sophisticated modern criminal schemes, particularly for identifying complex patterns in financial crimes and criminal networks, while also addressing the technical hurdles limiting the practical deployment of these models. This study underscores the critical necessity for the legal system to fortify procedural defenses against AI-generated misinformation and to accelerate the migration to quantum-resistant security infrastructures. Ultimately, this review highlights that preserving the validity of the justice system requires commitment to technological literacy and the establishment of rigorous verification frameworks to navigate the dual disruption of algorithmic probabilities and quantum insecurity.

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