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What is Keras API

Confluence of AI, Machine, and Deep Learning in Cyber Forensics
It allows to reduce cognitive load with best practices such as deep learning.
Published in Chapter:
Applications of Machine Learning in Cyber Forensics
Kishore Rajendiran (Sri Sivasubramaniya Nadar College of Engineering, India), Kumar Kannan (Vellore Institute of Technology, Vellore, India), and Yongbin Yu (University of Electronic Science and Technology of China, China)
Copyright: © 2021 |Pages: 18
DOI: 10.4018/978-1-7998-4900-1.ch002
Nowadays, individuals and organizations experience an increase in cyber-attacks. Combating such cybercrimes has become the greatest struggle for individual persons and organizations. Furthermore, the battle has heightened as cybercriminals have gone a step ahead, employing the complicated cyber-attack technique. These techniques are minute and unobtrusive in nature and habitually disguised as authentic requests and commands. The cyber-secure professionals and digital forensic investigators enforce by collecting large and complex pools of data to reveal the potential digital evidence (PDE) to combat these attacks and helps investigators to arrive at particular conclusions and/or decisions. In cyber forensics, the challenging issue is hard for the investigators to make conclusions as the big data often comes from multiple sources and in different file formats. The objective is to explore the possible applications of machine learning (ML) in cyber forensics and to discuss the various research issues, the solutions of which will serve out to provide better predictions for cyber forensics.
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