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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65037

AI powered cyber threat detection system

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65037

Volume:

10 |

6 |

Jun 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GHK

Greeshma H K

Master of computer application

UBDT college of Engineering

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Mentors

DMIHB

Dr. Md. Irshad Hussain B

Master of computer application

UBDT college of Engineering

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Abstract

The widespread adoption of digital technologies across various sectors has increased the risk of cyberattacks targeting computer networks and information systems. Organizations face numerous security challenges, including malware, phishing, ransomware, data breaches, and unauthorized access attempts. Traditional security solutions mainly rely on predefined rules and known attack signatures, making them less effective against emerging and previously unseen threats. As cyber threats become more sophisticated, the demand for intelligent and adaptive security mechanisms continues to grow. This study explores the role of artificial intelligence in cyber threat detection.

KEYWORDS

malware phishing ransomware data breaches

Cite This Article

Greeshma H K, Dr. Md. Irshad Hussain B, "AI powered cyber threat detection system," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-3, Jun 2026.

Full Article/Conclusion

The increasing number of cyber threats has created a strong need for advanced security solutions capable of protecting modern digital systems. Conventional security methods are often limited in their ability to identify emerging and sophisticated attacks, making intelligent detection mechanisms more important than ever. The overall analysis shows that AI-based threat detection systems can enhance the identification of malicious activities, support faster decision-making, and improve the efficiency of cybersecurity defenses. Although challenges such as data quality and evolving attack methods continue to exist, future developments in Artificial Intelligence are expected to further improve the effectiveness of cyber threat detection and contribute to a more secure digital environment.

References

[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th Edition, Pearson, 2021. [2] W. Stallings, Network Security Essentials: Applications and Standards, Pearson Education, 2022. [3] V. Kumar and S. Gupta, "Machine Learning Approaches for Intrusion Detection Systems," International Journal of Cyber Security, vol. 15, no. 2, pp. 45–58, 2023. [4] A. Sharma and R. Patel, "Artificial Intelligence in Cybersecurity: Opportunities and Challenges," Journal of Information Security Research, vol. 12, no. 1, pp. 23–36, 2024. [5] J. Brown, "Deep Learning Techniques for Network Intrusion Detection," IEEE Access, vol. 11, pp. 10215–10230, 2023.  

Editorial & Review Transparency

Publication Date

6/19/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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5

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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