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Temporal Analysis and Forecasting of Cyber Attack Intensity

Author(s):

Shrikant Khawshe , G H Raisoni College of Engineering; Vedanshu Thune, G H Raisoni College of Engineering; Yogvid Wankhede, G H Raisoni College of Engineering; Madhuri Sahu, G H Raisoni College of Engineering

Keywords:

Machine Learning, Multinomial Naïve-Bayes, React Native, Data Extraction, Text Classification, Firebase, NER

Abstract

As the frequency and sophistication of cyber-attacks continue to escalate in today's digital landscape, there is an urgent need for innovative approaches to understand and predict their intensity. This project focuses on leveraging temporal analysis techniques to forecast cyber-attack intensity by identifying patterns within historical data. Through the exploration of temporal correlations in attack volumes, the aim is to develop a robust forecasting system capable of anticipating future cyber incidents.

Other Details

Paper ID: IJSRDV12I30191
Published in: Volume : 12, Issue : 3
Publication Date: 01/06/2024
Page(s): 319-323

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