26 citations · 75 across the 10 of their papers we have counts for
10 papers
Deep Learning based Frameworks for Handling Imbalance in DGA, Email, and URL Data Analysis
Simran K, Prathiksha Balakrishna, Vinayakumar Ravi +1
Deep learning is a state of the art method for a lot of applications. The main issue is that most of the real-time data is highly imbalanced in nature. In order to avoid bias in tr…
Deep Learning Approach for Enhanced Cyber Threat Indicators in Twitter Stream
Simran K, Prathiksha Balakrishna, Vinayakumar R +1
In recent days, the amount of Cyber Security text data shared via social media resources mainly Twitter has increased. An accurate analysis of this data can help to develop cyber t…
Deep Learning Approach for Intelligent Named Entity Recognition of Cyber Security
Simran K, Sriram S, Vinayakumar R +1
In recent years, the amount of Cyber Security data generated in the form of unstructured texts, for example, social media resources, blogs, articles, and so on has exceptionally in…
A short review on Applications of Deep learning for Cyber security
Mohammed Harun Babu R, Vinayakumar R, Soman KP
Deep learning is an advanced model of traditional machine learning. This has the capability to extract optimal feature representation from raw input samples. This has been applied…
Emotion Detection using Data Driven Models
Naveenkumar K S, Vinayakumar R, Soman KP
Text is the major method that is used for communication now a days, each and every day lots of text are created. In this paper the text data is used for the classification of the e…
RNNSecureNet: Recurrent neural networks for Cyber security use-cases
Mohammed Harun Babu R, Vinayakumar R, Soman KP
Recurrent neural network (RNN) is an effective neural network in solving very complex supervised and unsupervised tasks. There has been a significant improvement in RNN field such…