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Digital forensics is the science of detecting evidence from digital
media like a computer, smart phone, server, or network. It provides
the forensic team with the most beneficial methods to solve
confused digital-related cases. AI and blockchain can be applied to
solve online predatory chat cases and photo forensics cases,
provide network service evidence, custody of digital files in
forensic medicine, and identify roots of data scavenging. The
increased use of PCs and extensive use of internet access, has
meant easy availability of hacking tools. Over the past two
decades, improvements in the information technology landscape have
made the collection, preservation, and analysis of digital evidence
extremely important. The traditional tools for solving cybercrimes
and preparing court cases are making investigations difficult. We
can use AI and blockchain design frameworks to make the digital
forensic process efficient and straightforward. AI features help
determine the contents of a picture, detect spam email messages and
recognize swatches of hard drives that could contain suspicious
files. Blockchain-based lawful evidence management schemes can
supervise the entire evidence flow of all of the court data. This
book can provide a wide-ranging overview of how AI and blockchain
can be used to solve problems in digital forensics using advanced
tools and applications available on the market.
This book provides theoretical background and state-of-the-art
findings in artificial intelligence and cybersecurity for industry
4.0 and helps in implementing AI-based cybersecurity applications.
Machine learning-based security approaches are vulnerable to poison
datasets which can be caused by a legitimate defender's
misclassification or attackers aiming to evade detection by
contaminating the training data set. There also exist gaps between
the test environment and the real world. Therefore, it is critical
to check the potentials and limitations of AI-based security
technologies in terms of metrics such as security, performance,
cost, time, and consider how to incorporate them into the real
world by addressing the gaps appropriately. This book focuses on
state-of-the-art findings from both academia and industry in big
data security relevant sciences, technologies, and applications.
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