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What is Botnet Forensics?
Botnets are harmful programs that are run by a botmaster or botherder, who is a malevolent programmer. Botherder infects the weak user's machine with a virus or viruses, the payload of which is a malicious program. It establishes contact with the command and control server and establishes a connection with it. Spammers pay the botherder for their services, and the botherder then issues the updated command. Botnet forensics is concerned with investigating botnet attacks and their associated vulnerabilities after they have occurred. Botnet forensics is critical these days, as it aids and protects the business from both external and internal network assaults.
What is Botnet Forensics, and how does it work?
Botnet forensics is the science that identifies the breadth of a breach and uses techniques to detect the infection type. It is a botnet assault investigation that involves operations such as collection, identification, detection, acquisition, and attribution. Botnet forensics' main goal is to assess the severity of intrusions, investigate them, and provide information on how to recover from them to improve system security.
The Botnet Forensics data may be used to do the following:
Tools for security should be improved.
Recognizing the modus operandi.
In the future, it may be utilized to prevent a network security threat.
Botnet forensics not only ensures network security but also facilitates law enforcement.
Botnet Forensics System Classification
The following categories may be used to categorize all Botnet Forensics research in general −
Payload-Based Classification
In this method, packets are categorized according to the payload's field. The payload employs classification techniques such as Deep Packet Inspection, which uses signature analysis for traffic verification and categorization. There are several forms of signature analysis −
Heuristic Analysis
It entails monitoring network traffic to detect suspicious network traffic and, using a processor based on a heuristic analysis, detect a bot of suspicious network traffic behavior. Command and control traffic linked with a botmaster is included in this suspicious network traffic pattern. Heuristic and behavioral analysis are complementary. For detecting the virus and infection, some antivirus software uses both approaches.
Behavioral Analysis
Behavioral analysis and heuristic analysis are used in tandem by various antivirus programs to detect viruses and infections.
Pattern Analysis
In the payload of packets, applications contain various patterns that may be utilized to identify protocols. The pattern might appear at any point in the packet.
Numerical Analysis
This entails considering numerical features. Numerical packets like Payload size, the number of response packets, etc.
The main goal is to discover a bit of string functioning in the provided payload, study its nature, and determine its characteristics. This categorization approach was utilized on the free zone, a free network service provider run by Fredericton.
Classification Using Decision Trees
A decision tree is produced simultaneously as the data is divided into smaller subgroups in this technique. The final result is displayed as a tree with decision nodes and leaf nodes. This is the ideal approach to utilize for categorization when dealing with unknown traffic.
Classification Using Ensembles
Rokach et al. split the ensemble model into dependent and independent methods. The most well- known model instance in the Dependent approach is boosting, often known as resampling and combining. It is used to enhance week classification performance on dispersed training data. AdaBoost is a well-known ensemble technique for improving a basic boosting algorithm through an iterative process. Bagging and Wagging are two well-known independent methods.
Five steps to the Botnet Forensic Framework
Malware
The Malware phase is the first. The steps of malware dissemination, infection, communication, and assault are all included. The most popular and extensively used channel is IRC. This step identifies whether the malware is a botnet or another form of malware.
Botnet Forensic Investigator
The second step of the Botnet Forensics Framework is the Botnet Forensic Investigator. The focus of this phase is on −
Detecting whether the system has been hacked or infected.
If the system is hacked, it will determine if the attack is a bot or another sort of assault.
It looks for the bot by looking at traffic, attribution, automotive passive, and malware samples.
It also focuses on Attribution, Automotive passive, and Malware Sample.
Botnet Forensic Analyzer
The Botnet Forensics Framework is now in its third phase. This stage entails −
Taking a look at the findings of the identifier phase.
It is used to search after a criminal investigation has been completed.
If the identifier detects a malware, the analyst will investigate what kind of malware it is and where it infected.
It combines hints with real-world data and sends all of the specifics to the Botnet Evidence Phase.
Analysis, inquiry, inspection, collecting, and preservation are all phases in this phase.
Botnet Evidence
The Botnet Forensics Framework is now in its fourth phase. This step compiles all of the data from the previous stages and sends it to the Incident Response Phase 3.
Incident Action
The Botnet Forensics Framework is now in its final phase. Containment, eradication, and recovery are the three actions that make up this phase. The steps in this phase are as follows −
The IR team will begin combating the danger after they have gathered all of the facts and obtained a thorough knowledge of the situation.
It entails taking steps to avert additional harm.
Once the danger has been handled, the next step is to restore normal functioning to the systems by increasing network security, rebuilding systems, and replacing compromised files.
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