The Identification of Network Intrusions with Generative Artificial Intelligence Approach for Cybersecurity

Himanshu Sinha

doi:10.48001/jowacs.2024.2220-29

Authors

Himanshu Sinha Kelley School of Business, Indiana University, Bloomington, Naperville IL, Unites States

DOI:

https://doi.org/10.48001/jowacs.2024.2220-29

Keywords:

Artificial Intelligence (AI), Cybersecurity, Generative adversarial network, Generative artificial intelligence, Network intrusion detection

Abstract

Generative Artificial Intelligence (Generative AI) offers a paradigm shift to the way robots perceive and interact with data. Generative AI approaches aim to produce new data samples that closely match the original dataset, in contrast to standard AI models that concentrate on tasks such as categorisation or prediction. This ability has broad implications for a variety of fields, including network security. New generation of network intrusion defense brought forth by Generative AI is revolution using the area of network security. In this work, investigates the revolutionary potential of Generative AI in network intrusion detection, with the goal of developing a proactive and adaptable cyber protection mechanism. In this work the use of Generative AI use for identifying network intrusions, using the NSL-KDD dataset. The work begins with meticulous data preprocessing using handling missing values, encoding, feature scaling, and feature extraction to enhance the dataset and then focuses on using Generative AI for intrusion detection. In this work many models have been used like SVM, AE, DAE, and GANs, and in this GANs has the best accuracy with 91.12% compared with other models.

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Author Biography

Himanshu Sinha, Kelley School of Business, Indiana University, Bloomington, Naperville IL, Unites States

Himanshu Sinha is the Director of Advanced Data Science at Marriott International, bringing over two decades of expertise in advanced analytics and machine learning to the role. His career highlights include developing influential frameworks at CVS Healthcare and Precisely, with a focus on deep learning, tree-based algorithms, natural language processing (NLP), and other advanced methodologies.

Mr. Sinha holds a Master of Science from Indiana University and has further honed his skills with certifications from Johns Hopkins University. He has an extensive publication record, with numerous research papers featured in esteemed national and international journals and conferences. His profound knowledge of Artificial Intelligence and commitment to the field keep him at the forefront of the latest technological advancements and trends.

Contact Information:

Email: himanshusin@gmail.com , hisinha@alumni.iu.edu

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