Cyberattacks Prediction with Machine Learning

A cyber-attack occurs when an organization uses cyberspace to disrupt, disrupted, disable, damage, or manipulate the infrastructure; This also occurs when the integrity of the data is destroyed or controlled information is stolen. The current state of cyberspace reflects uncertainty about the future of the Internet and its rapidly growing user base. New paradigms cause more concerns because the large data collected by the gadget sensors reveals a lot of information that can be used for concentrated attacks. Although the mounds of the extinct approach, models and algorithms have provided the basis for predictions for cyberbulder, must consider new models and algorithms, which are based on data deficiencies other than work techniques. However, the non-regional information processing architecture can be adapted to learn different data representations of network traffic to classify the type of network attacks.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-22
DOI
https://doi.org/10.22214/ijraset.2025.68992
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Cyberattacks Prediction with Machine Learning

Praveen Kumar Prajapati
International Journal for Research in Applied Science and Engineering Technology
Network Security and Intrusion Detection
article

Cyberattacks Prediction with Machine Learning

Praveen Kumar Prajapati
article en

Abstract

A cyber-attack occurs when an organization uses cyberspace to disrupt, disrupted, disable, damage, or manipulate the infrastructure; This also occurs when the integrity of the data is destroyed or controlled information is stolen. The current state of cyberspace reflects uncertainty about the future of the Internet and its rapidly growing user base. New paradigms cause more concerns because the large data collected by the gadget sensors reveals a lot of information that can be used for concentrated attacks. Although the mounds of the extinct approach, models and algorithms have provided the basis for predictions for cyberbulder, must consider new models and algorithms, which are based on data deficiencies other than work techniques. However, the non-regional information processing architecture can be adapted to learn different data representations of network traffic to classify the type of network attacks.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 92%
Network Security and Intrusion Detection
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