Please use this identifier to cite or link to this item: http://localhost:8081/jspui/handle/123456789/18562
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dc.contributor.authorSingh, Updesh-
dc.date.accessioned2025-12-18T07:03:42Z-
dc.date.available2025-12-18T07:03:42Z-
dc.date.issued2024-06-
dc.identifier.urihttp://localhost:8081/jspui/handle/123456789/18562-
dc.guideGangopadhyay, Sugataen_US
dc.description.abstractAs cyber threats become more advanced, the need for better malware detection methods grows. This dissertation, titled ”Advancing Cybersecurity: AI-Powered Malware Detection,” explores how artificial intelligence (AI) can improve the way we detect and prevent malware. The main goal is to develop and assess AI techniques that can efficiently identify and mitigate new types of malware compared to traditional methods. Several deep learning and machine learning models were implemented and assessed using a carefully chosen dataset of malware samples. The findings indicate that AI-driven detection systems outperform traditional approaches in accuracy, speed, and adaptability. This research aims to leverage AI’s analytical capabilities to devise practical solutions for building resilient defenses against evolving cyber threats, aiming to enhance the safety of digital environments.en_US
dc.language.isoenen_US
dc.publisherIIT, Roorkeeen_US
dc.titleADVANCING CYBER SECURITY: AI POWERED MALWARE DETECTIONen_US
dc.typeDissertationsen_US
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