AUTOMATED CYBER BREACH PREDICTION AND CLASSIFICATION SYSTEM USING DEEP LEARNING
Ganesh Rokaya
, Gajjeli Varun Kumar , E Trinath , E Uma Maheswara Reddy , R Nivetha
Classification, Cyberattacks, Deep Learning, Protection, Recovery
Analyzing cyber incident data sets is an important method for deepening our understanding of the evolution of the threat situation. In present generation we come to know about many cyber breaches and hacking taking place. In this project work, we research about the various cyber-attacks and breaches and study the way these attacks are done and find an alternative for the same. We show that rather than by distributing these attacks as because they exhibit autocorrelations, we should model by stochastic process both the hacking breach incident inter- arrival times and breach sizes. We draw a set of cyber securities insights, including that the threat of cyber hacks is indeed getting worse in terms of their frequency. In our project we will be using the algorithms such as Convolution Neural Network (CNN), and Recurrent Neural Network (RNN) for analyzing our results.
"AUTOMATED CYBER BREACH PREDICTION AND CLASSIFICATION SYSTEM USING DEEP LEARNING", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 3, page no.1035 - 1042, March-2024, Available :https://ijsdr.org/papers/IJSDR2403145.pdf
Volume 9
Issue 3,
March-2024
Pages : 1035 - 1042
Paper Reg. ID: IJSDR_210618
Published Paper Id: IJSDR2403145
Downloads: 000347085
Research Area: Engineering
Country: Tambaram, Chengalpattu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
