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Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions
Congratulations to Syed Rizvi and co-authors Mark Scanlon, Jimmy McGibney, and John Sheppard on the publication of Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions in IEEE Access.
Co-authors: Mark Scanlon, Jimmy McGibney, and John Sheppard.
AI-generated summary of the contribution: This paper presents a comprehensive survey of the application of artificial intelligence (AI) in network forensics, covering expert systems, machine learning, deep learning, and ensemble/hybrid approaches. The study discusses the current challenges and future directions in network forensics, including network traffic analysis, intrusion detection systems, and Internet-of-Things devices. The paper provides an overview of the state-of-the-art in network forensics and the application of AI in various domains, including vehicular networks and smart grids. It also highlights the importance of AI in network forensics, including its ability to improve the performance of network forensic classifications and assist in the investigation of network traffic. The paper is organized into three primary sections, including a discussion of publicly available datasets for network forensics, an overview of the state-of-the-art in AI applications in network forensics, and a summary of the current challenges and future directions in network forensics.