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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

AI -BASED NOVEL COGNITIVE COMPUTATIONAL STRATEGY FOR OPTIMIZING BRAIN TUMOR CLASSIFICATION USING MAGNETIC RESONANCE IMAGING DATA

SEDHUPATHI S JANAKIRAMAN M PREMNATH RS VIGNESH R

Bachelor of Engineering in Computer Science And Engineering

The Kavery Engineering College

(An Autonomous Institution, affiliated to Anna University Chennai and Approved by AICTE, New Delhi) MECHERI, SALEM-636453
DOI:https://doi.org/10.55041/ijcope.v2i4.589

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

The    rapid     expansion    of   digital    infrastructure,    network    security has become a critical challenge. Traditional intrusion detection systems (IDS) often struggle with high false-positive rates and poor adaptability to new attack patterns. To address these issues, this paper proposes an enhanced AI-based Network Intrusion Detection System (NIDS) using Generative Adversarial Networks (GANs). GANs, consisting of a generator and a discriminator, enable the system to detect anomalies more effectively by learning complex attack patterns from network traffic data. The generator produces synthetic attack scenarios, improving the model’s ability to recognize both known and novel threats, while the discriminator distinguishes between legitimate and malicious traffic. Unlike conventional machine learning-based IDS, which rely on static datasets, the proposed system continuously evolves, improving its detection accuracy over time.

How to Cite this Paper

S, S., M, J., RS, P. & R, V. (2026). AI -Based Novel Cognitive Computational Strategy for Optimizing Brain Tumor Classification Using Magnetic Resonance Imaging Data. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.589

S, SEDHUPATHI, et al.. "AI -Based Novel Cognitive Computational Strategy for Optimizing Brain Tumor Classification Using Magnetic Resonance Imaging Data." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.589.

S, SEDHUPATHI,JANAKIRAMAN M,PREMNATH RS, and VIGNESH R. "AI -Based Novel Cognitive Computational Strategy for Optimizing Brain Tumor Classification Using Magnetic Resonance Imaging Data." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.589.

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References


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  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Apr 26 2026
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