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Quantum-AI cybersecurity threat detection framework: A hybrid architecture for enterprise security operations.

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Title: Quantum-AI cybersecurity threat detection framework: A hybrid architecture for enterprise security operations.
Authors: Shaik, Muneer Basha reachme.muneer@gmail.com
Source: International Journal of Electrical & Computer Engineering (2088-8708). Oct2026, Vol. 16 Issue 5, p2672-2679. 8p.
Subjects: Quantum computing, Anomaly detection (Computer security), Hybrid computers (Computer architecture), Cryptography, Internet security
Abstract: Enterprise security operations face computational bottlenecks that classical architectures cannot efficiently resolve at scale. This paper presents the quantum-AI cybersecurity threat detection framework (QACTDF), a hybrid architecture that combines quantum-enhanced optimization with AI-driven behavioral analytics for large-enterprise threat detection. The architecture employs a four-layer orchestration model in which an AI-governed routing policy selectively directs security workloads-including threat correlation, cryptographic verification, and anomaly classification-to quantum-assisted processors, while high-throughput tasks such as telemetry ingestion and alert triage are handled by classical infrastructure. Qualitatively evaluated against canonical security framework criteria-detection scope, integration feasibility, scalability, and sustainability-and supported by simulation-derived performance estimates, QACTDF addresses functional capability gaps in conventional security architectures. The framework additionally incorporates post-quantum cryptographic alignment in accordance with NIST FIPS 203 and provides a sequential adoption pathway for enterprise architects integrating quantum capabilities into existing security operations centers. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Quantum-AI cybersecurity threat detection framework: A hybrid architecture for enterprise security operations.
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  Data: <searchLink fieldCode="AR" term="%22Shaik%2C+Muneer+Basha%22">Shaik, Muneer Basha</searchLink><i> reachme.muneer@gmail.com</i>
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  Data: <searchLink fieldCode="DE" term="%22Quantum+computing%22">Quantum computing</searchLink><br /><searchLink fieldCode="DE" term="%22Anomaly+detection+%28Computer+security%29%22">Anomaly detection (Computer security)</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+computers+%28Computer+architecture%29%22">Hybrid computers (Computer architecture)</searchLink><br /><searchLink fieldCode="DE" term="%22Cryptography%22">Cryptography</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink>
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  Data: Enterprise security operations face computational bottlenecks that classical architectures cannot efficiently resolve at scale. This paper presents the quantum-AI cybersecurity threat detection framework (QACTDF), a hybrid architecture that combines quantum-enhanced optimization with AI-driven behavioral analytics for large-enterprise threat detection. The architecture employs a four-layer orchestration model in which an AI-governed routing policy selectively directs security workloads-including threat correlation, cryptographic verification, and anomaly classification-to quantum-assisted processors, while high-throughput tasks such as telemetry ingestion and alert triage are handled by classical infrastructure. Qualitatively evaluated against canonical security framework criteria-detection scope, integration feasibility, scalability, and sustainability-and supported by simulation-derived performance estimates, QACTDF addresses functional capability gaps in conventional security architectures. The framework additionally incorporates post-quantum cryptographic alignment in accordance with NIST FIPS 203 and provides a sequential adoption pathway for enterprise architects integrating quantum capabilities into existing security operations centers. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.11591/ijece.v16i5.pp2672-2679
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        Text: English
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      – SubjectFull: Quantum computing
        Type: general
      – SubjectFull: Anomaly detection (Computer security)
        Type: general
      – SubjectFull: Hybrid computers (Computer architecture)
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      – SubjectFull: Cryptography
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      – SubjectFull: Internet security
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              Text: Oct2026
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