Authors : Anusha Yella

Volume/Issue : Volume 10 - 2025, Issue 6 - June

Google Scholar : https://tinyurl.com/mr3evah4

DOI : https://doi.org/10.38124/ijisrt/25jun698

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : With greater dependence on technology and the availability of internet connectivity, attacks over the network have increased, so it is essential to be able to mitigate these threats. It is a time-consuming process that involves constant monitoring and immediate responses for possible incidents. With intelligent and proactive network security on the table, artificial intelligence (AI) is beginning to rise as a probable answer. AI systems can process such a huge pack of data in seconds, detecting strange shapes - or alerts encourage the need for any action usually to be taken. It helps ensure the vulnerabilities, when detected, can be mitigated in time, preventing further damage to networks out of these anomalies. Because AI can learn from data and adapt or evolve its model based on new ant patterns, it is very good at spotting emerging threats using machine learning algorithms. It can also help differentiate between actual attacks and false alarms, reducing the time and resources needed for manual verification. This smart way to handle network security increases threat detection efficiency and accuracy while at the same time decreasing response times, which serves to reduce attack impact alongside damage.

Keywords : Dependence, Availability, Intelligence, Differentiate, Accuracy.

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