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Learning Network Forensics

Learning Network Forensics

By : Datt
1.5 (2)
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Learning Network Forensics

Learning Network Forensics

1.5 (2)
By: Datt

Overview of this book

We live in a highly networked world. Every digital device—phone, tablet, or computer is connected to each other, in one way or another. In this new age of connected networks, there is network crime. Network forensics is the brave new frontier of digital investigation and information security professionals to extend their abilities to catch miscreants on the network. The book starts with an introduction to the world of network forensics and investigations. You will begin by getting an understanding of how to gather both physical and virtual evidence, intercepting and analyzing network data, wireless data packets, investigating intrusions, and so on. You will further explore the technology, tools, and investigating methods using malware forensics, network tunneling, and behaviors. By the end of the book, you will gain a complete understanding of how to successfully close a case.
Table of Contents (12 chapters)
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11
Index

Trends in the evolution of malware


Malware has a very interesting history.

In 1949, an American scientist of Hungarian origin, John von Neumann, wrote Theory of Self-Reproducing Automata. In 1971, this theory formed the basis of an experiment on the creation of the first self-replicating computer program. This program was called the Creeper system, where it gained access to the target computers via the Advanced Research Projects Agency Network (ARPANET) and copied itself with the I'm the creeper, catch me if you can message.

An additional piece of interesting information about John von Neumann is that he later on went on to be a part of the Manhattan Project and helped in the design of atom bombs that ended the Second World War and directed the world towards Nuclearization.

While a nuclear war is a sure way to head towards mutual assured destruction (MAD), the cyber war of malware has just been escalating since it began. With no means of MAD or even attribution in a lot of cases, the attackers...

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Learning Network Forensics
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