docx
keyboard_arrow_up
School
University of Phoenix *
*We aren’t endorsed by this school
Course
140
Subject
Information Systems
Date
Dec 6, 2023
Type
docx
Pages
2
Uploaded by EarlFlowerAlligator27
Python is a flexible programming language that is frequently utilized in the field of cybersecurity due to its user-friendliness, extensive library, and support from the community. It also provides a few benefits that can assist in the defense of networks
against cyberattacks. Let's look at the scenario of a Distributed Denial of Service (DDoS) attack as an illustration of how Python can help in the defense against such attacks. After that, we'll talk about how Python is useful in network forensics, with a particular emphasis on the investigation process.
Defending Against Distributed Denial of Service Attacks,
An attempt to overwhelm a network, service, or website with a flood of incoming traffic from multiple sources is an example of a distributed denial of service, or DDoS, attack. This makes it impossible for legitimate users to access the targeted resource. The following are some of the ways that using Python to defend against DDoS attacks can be beneficial:
Analysis of Incoming Traffic Patterns and Filtering of It Python enables network administrators to develop custom scripts and tools for analyzing and filtering different types of incoming traffic. Administrators can swiftly respond to a distributed denial of service (DDoS) attack by filtering out malicious traffic using tools such as firewalls and intrusion prevention systems by monitoring network traffic and identifying patterns that are consistent with such an attack.
Investigative steps in network forensics are as follows:
The investigation of network-related incidents, such as security breaches or cyberattacks, is part of the field of network forensics. The goal of this investigation is to determine the underlying cause of the incident, as well as its scope and impact. The Packet Capture and Analysis process is an essential part of network forensics and is one of its key processes.
Packet Capture and Analysis: This first step involves capturing and analyzing network packets to reconstruct the sequence of events that took place during a cybersecurity incident. Because it contains libraries such as Scapy, which makes it possible to manipulate and craft packets, Python is an extremely helpful tool for carrying out this process. Writing Python scripts allows for the capturing of network packets, the extraction of relevant information, and the reconstruction of communication patterns. These scripts can be used to assist in locating the origin of
an attack, as well as the methods and vulnerabilities that were taken advantage of.
In this stage of the process, the capabilities of Python make it much simpler to automate the analysis of a large volume of packets, filter out data that is not relevant to the investigation, and concentrate on the packets that contain information that is relevant to the investigation. In addition, the incorporation of data visualization libraries into Python makes it possible to present intricate packet relationships in a format that is easier to comprehend, which assists investigators in
drawing conclusions based on the data that was captured.
When it comes to defending networks against cyberattacks like DDoS and performing network forensics tasks like packet capture and analysis, Python's advantages, such as its ease of use, extensive libraries, and community support,
contribute to its effectiveness. Because of these benefits, cybersecurity professionals can respond rapidly and efficiently to incidents, which improves the network's overall security
posture.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help