Book Image

Learning Network Forensics

By : Samir Datt
Book Image

Learning Network Forensics

By: Samir 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 (17 chapters)
Learning Network Forensics
About the Author
About the Reviewers

Future of network forensics

While it is difficult to predict the future, some trends are self-evident. Let's take a look at them.

Organizations are moving to higher speed and bandwidth networks. More and more data is traveling over the networks and to and from a variety of devices.

IPv6 is here to stay! It brings along a proliferation of Internet-connected devices, right from your toaster, TV, refrigerator, photocopier, and coffee machine to your security and alarm system. This is known as the Internet of Things or IoT for short.

It does not require much crystal ball gazing to determine the trends of things to come in the network forensics domain. As a large number of devices get networked, there is going to be larger roles for Network Forensic 007s. We will be looking at more and more connected devices, the evidence that they store, the way that they act, and the way they are affected by different compromises. We will be collecting, handling, preserving, and analyzing large volumes of data...