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Table 2 Briefly describe all of the attack classes in the UNSW-NB15 dataset

From: Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

Attack categories

Brief description

Fuzzers

By supplying a vast volume of random data, the insider tries to crash a software, operating system, or network

Backdoor

Cyber attackers can get illegal access to websites using this form of software. By focusing on vulnerable entry points, the intruders were able to disseminate malware throughout the system

Analysis

Pay special attention to malware attacks and computer intrusions in which attackers gain permissions by utilizing their technological capabilities

Reconnaissance

Gathers data on system flaws that can be used to gain control of the system

Exploit

A piece of software that exploits security flaws and vulnerabilities. An attacker can gain unrestricted access with this attack

Generic

Has the ability to decrypt all block ciphers without having to know the cipher’s structure

DoS

User access to machines and network resources can be suspended by an attacker. By delivering too much confusing traffic, the attacker overwhelms the network

Shellcode

It is a sequence of instructions that executes software commands to harm a machine

Worm

It includes security flaws that attack the host machine and spread throughout the network. It is capable of exploiting many applications’ security flaws