CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023

CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023 Digital forensics is the application of investigative and analytical techniques .

There are many tools available for digital forensics CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023:

EnCase is widely used by forensic experts in the Codec Network as part of digital forensics. The Codec Network provides a professional training platform where young undergraduates and entry-level managers are nurtured with the latest practical tools and in-depth cybersecurity expertise and knowledge to excel alongside our industry professionals.

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Phases of computer forensics CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

The various and distinct phases of computer forensics are
1. Collection – Collection of evidence from the crime scene. Evidence includes hard drive, laptops, cell phones, computers, books and other accessories CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

Preservation – The preservation of evidence related to a crime scene. This phase involves imaging hard drives or other digital devices, marking the evidence collected, and then safely storing the evidence in a well-protected (safe and secure) environment CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.
Filtering – May also be called “Analysis”. It is a process where the evidence (data) is filtered and only the evidence (data) related to the crime is analyzed and the rest of the data is not considered for further investigation.
Report – It is the final step in the digital forensics process CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023..

It is summarized in the preparation of a report that contains all the results, procedures or steps that have been taken and documents all the methods and tools that are used to collect and obtain the evidence. This stage is the most important to avoid questioning the integrity of the investigation and investigation in court CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

EnCase overview

EnCase Forensics is a very popular software and is widely accepted in court in forensic investigations. EnCase comes with many features that help in all four phases of forensic investigation CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

EnCase properties

EnCase features and supported operating systems are:

Supported operating systems Windows 95/98/NT/2000/XP/2003 Server, Linux Kernel 2.4 and higher, Solaris 8/9 both 32 and 64 bit, AIX, OSX
Supported file systems FAT12/16/32, NTFS, EXT2/3 (Linux), Reiser (Linux), UFS (Sun Solaris), AIX journaling file system (JFS, jfs), LVM8, FFS (OpenBSD, NetBSD and FreeBSD), Palm, HFS, HFS+ (Macintosh), CDFS, ISO 9660, UDF, DVD, and TiVo 1 and TiVo 2. Now supports the Novell file system.
File Type Support – Supports over 400 different file formats. It now supports Microsoft Office 2007 documents and the mbox format, which is quite common among mail user agents.
Image Formats VMware, dd and Safeback v2 image formats also support CD/DVD. Now supports the LinEn tool for Linux systems
Internet and email support Hotmail, Outlook, Lotus Notes, Yahoo, AOL, Netscape, mbox and Outlook Express) and supports Internet Explorer, Mozilla, Opera and Safari
Gallery View Displays BMP, JPG, GIF, and TIFF images CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

Forensic process using EnCase

Collection: With EnCase, data can be collected using a hard drive, floppy disk, pen, CD-ROM, digital camera, memory card, and other digital devices.
Conservation: In this
Step 1) Open EnCase forensic-710 and click add local device. If a write blocker is attached to the machine and digital device, check option 1, 2 and 5, otherwise uncheck all and click Next.

Step 2) Check the box in the name column that shows the connected device name or label like (1,2,3 or any numerical number) and click finish CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023..

Step 3) now to open the records click on the device tag number which is displayed in the “name” column and again right click on the tag number and select get CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

Step 4), then a three-tab pop-up will appear. On the location tab, fill in all the fields. If you want to encrypt the evidence file, enable the Compression field on the Format tab, otherwise disable it. In the Verification Hash field, MD5 and SHA1 should be selected after clicking the OK button CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

Step 5) then the image creation will start and the time required to create the image will be displayed on the bottom right.

Step 6) After creating the image, the device will automatically disconnect. The image will be saved in the folder whose path we set earlier CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

Filtering:
Step 7) now using this image the data will be filtered and analyzed for further investigation.

Message: A message will appear on the left side of the bottom

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Content
In real life, all the data we collect is in large quantities. To make sense of this data, we need a process. It is not possible to process them manually. This is where the concept of feature extraction comes into play.

Let’s say you want to work with some of the big machine learning projects or the most amazing and popular domains like deep learning where you can use images to create an object detection project. Creating projects on computer vision, where you can work with thousands of interesting projects in a set of image data CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023..

To work with them, you need to go to feature extraction, take a course in digital image processing, and learn image processing in Python, which will make your life easier. Upskilling with a free online course will help you understand the concepts clearly CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

So let’s see how we can use this technique in a real scenario.

What is feature extraction?
Why is feature extraction useful?
An application of feature extraction
How to save images to the machine?
How to use feature extraction technique for image data: Features as grayscale pixel values
How to extract features from image data: What is the mean pixel value of the channels
A project using the feature extraction technique
Image feature detection using OpenCV
What is feature extraction?
Feature extraction is part of the dimensionality reduction process in which the initial set of raw data is split and reduced into more manageable groups. So when you want to process it will be easier. The most important characteristic of these large data sets is that they have a large number of variables.

These variables require a lot of computing resources to process. Thus, feature extraction helps extract the best features from these large data sets by selecting and combining variables into features, effectively reducing the amount of data CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

These functions are easy to process, but still able to accurately and original describe the current data set.

Why is feature extraction useful?

The feature extraction technique is useful when you have a large data set and need to reduce the number of sources without losing any important or relevant information. Feature extraction helps reduce the amount of redundant data from a dataset.

Ultimately, data reduction helps build a model with less machine effort and also increases the speed of learning and generalization of steps in the machine learning process.

Application of feature extraction
Bag of Words- Bag-of-Words is the most widely used natural language processing technique. In this process, they extract words or features from a sentence, document, web page, etc. and then rank them by frequency of use.

So in this whole process, feature extraction is one of the most important parts.
Image Processing – Image processing is one of the best and most interesting fields. In this domain, you basically start playing with your images to understand them.

So here we use many techniques that also include feature extraction and algorithms to detect features like shapes, edges or motion in a digital image or video to process them.
Autoencoders CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023:

The main purpose of autoencoders is to efficiently encode data, which is inherently unattended. this process falls under unsupervised learning. Here, then, a feature extraction procedure is applicable to identify key features from data to code by learning from the coding of the original dataset and inferring new ones.

How to save images to the machine?
So in this section, we’ll start from scratch. First we need to understand how a machine can read and store images. Loading an image, reading it and then processing it with a machine is difficult because a machine doesn’t have eyes like we do.

Let’s see how the machine understands the image.

Machines see any images in the form of a matrix of numbers. The size of this matrix actually depends on the number of pixels of the input image.

What is a pixel?

The pixel values ​​for each of the pixels represent or describe how bright the pixel is and what color it should be. So in the simplest case of binary images, the pixel value is a 1-bit number indicating either foreground or background.

So pixels are numbers or pixel values ​​that indicate the intensity or brightness of a pixel.

Smaller numbers closer to zero help represent black, and larger numbers closer to 255 indicate white.

This is the concept of pixels and how a machine sees images without eyes through numbers.

feature extraction in image processing
The dimensions of the image are 28 x 28. And if you want to check it, you can check the number of pixels.

But for the case of a color image, we have three matrices or channels

red,
Green
and Blue.
So in these three matrices, each of the matrices has values ​​between 0-255, representing the color intensity of that pixel CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.

If you have a color image like the dog image we have in the top left image. so as a human you have eyes so you can see and you can tell it’s a dog color image. But how can a computer understand that it is a color or black and white image CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023?

So you can see that we also have three matrices that represent the RGB channel – (for the three color channels – red, green and blue) On the right we have three matrices. These three channels overlap and are used to create a color image. So this is how a computer can distinguish between images.

Let’s see an example of how we can run the code using Pythonimport pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib embedded

from skimage.io import imread, imshow
image = imread(‘https://d1m75rqqgidzqn.cloudfront.net/content/sample_image.png’, as_gray=True)
imshow (image)
feature extraction in image processing
Check the image shape:#check image shape
print (image.shape)

print (picture)
Image shape: (1480, 1490)

Field:

[[0.96862745 0.96862745 0.79215686 … 0.96862745 1. 1. ] [0.96862745 0.96862745 0.79215686 … 0.96862745 1. 1. ] [0.79215686 0.79215686 0. … 0.79215686 1. 1. ] … [0.89019608 0.89019608 0. … 0.89019608 1. 1. ] [0.8745098 0.8745098 0. … 0.8745098 1. 1. ] [0.8745098 0.8745098 0. … 0.8745098 1. 1. ]]

How to use feature extraction technique for image data: Features as grayscale pixel value
If we use the same example as our image that we use above in the section – the dimension of the image is 28 x 28, right? But can you guess the number of features in this image CREATING IMAGE & DATA EXTRACTION OF DIGITAL DEVICE 2023.?

The number of features is the same as the number of pixels, so the number will be 784

So now I have one more important question –

how do we declare these 784 pixels as features of this image? Do you ever think about it?

So the solution is that you can simply concatenate each pixel value one by one to generate a feature vector for the image. Let’s imagine t

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