AI Cyber Security: Enhancing Network Security with Deep Learning for Real-Time Threat Detection and Performance Evaluation

AI Cyber Security: Enhancing Network Security with Deep Learning for Real-Time Threat Detection and Performance Evaluation

연구 분야: Safety

학회: 2024 3rd International Conference for Advancement in Technology (ICONAT)

In an era characterized by persistent cyberthreats, artificial intelligence (AI) integration into cybersecurity has become a critical tactic to improve threat detection and response capabilities. This study investigates the significant impact of AI on cybersecurity, with an emphasis on how it is developing methods for detecting and countering threats. By leveraging machine learning algorithms, natural language processing, and anomaly detection techniques, artificial intelligence (AI) empowers cybersecurity systems to examine large datasets, identify trends, and proactively mitigate advanced cyberattacks. In order to highlight AI’s efficacy in countering developing threats, this study looks at how it is being applied in a number of cybersecurity sectors, such as network security, endpoint protection, and behavioral analytics. The intricacies and moral dilemmas of AI-powered cybersecurity solutions are also covered, emphasizing the necessity of strong governance structures and ethical AI practices to guarantee efficacy and reduce unforeseen repercussions. The adoption of AI as a cybersecurity force multiplier is ultimately highlighted in this paper, which also advocates for continued research and cooperation to fully realize AI’s promise in protecting digital assets and infrastructure against new threats.