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Jain et al., 2025 - Google Patents

Designing a hybrid neural network framework for real-time anomaly detection in cybersecurity applications

Jain et al., 2025

Document ID
2779189269247980289
Author
Jain A
Ead W
Alshahrani M
Altamimi J
Aklan F
Rihan S
Publication year
Publication venue
International Journal of Information Technology

External Links

Snippet

As cybersecurity is becoming a prominent domain, it is an imperative to provide real-time anomaly detection for early threat detection and to keep networks safe. In this paper, an optimized hybrid neural network-framework is proposed to detect anomalies at several …
Continue reading at link.springer.com (other versions)

Classifications

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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416—Event detection, e.g. attack signature detection
    • H—ELECTRICITY
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    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425—Traffic logging, e.g. anomaly detection
    • G—PHYSICS
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    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/562—Static detection
    • G06F21/563—Static detection by source code analysis
    • H—ELECTRICITY
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • G06F21/554—Detecting local intrusion or implementing counter-measures involving event detection and direct action
    • H—ELECTRICITY
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    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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