Cargando…
Cyber attack evaluation dataset for deep packet inspection and analysis
To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cy...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720441/ https://www.ncbi.nlm.nih.gov/pubmed/36478690 http://dx.doi.org/10.1016/j.dib.2022.108771 |
_version_ | 1784843558184812544 |
---|---|
author | Shandilya, Shishir Kumar Ganguli, Chirag Izonin, Ivan Nagar, Prof. Atulya Kumar |
author_facet | Shandilya, Shishir Kumar Ganguli, Chirag Izonin, Ivan Nagar, Prof. Atulya Kumar |
author_sort | Shandilya, Shishir Kumar |
collection | PubMed |
description | To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cyber attacks to enable experimentation on challenges based on implementing defense mechanisms on a larger scale. For collecting the data, we captured the network traffic of configured virtual machines using Wireshark and tcpdump. To analyze the impact of several cyber attack scenarios, this dataset presents a set of ten computers connected to Router1 on VLAN1 in a Docker Bridge network, that try and exploit each other. It includes browsing the web and downloading foreign packages including malicious ones. Also, services like File Transfer Protocol (FTP) and Secure Shell (SSH) were exploited using several attack mechanisms. The presented dataset shows the importance of updating and patching systems to protect themselves to a greater extent, by following attack tactics on older versions of packages as compared to the newer and updated ones. This dataset also includes an Apache Server hosted on a different subset of VLAN2 which is connected to the VLAN1 to demonstrate isolation and cross- VLAN communication. The services on this web server were also exploited by the previously stated ten computers. The attack types include Distributed Denial of Service, SQL Injection, Account Takeover, Service Exploitation (SSH, FTP), DNS and ARP Spoofing, Scanning and Firewall Searching and Indexing (using Nmap), Hammering the services to brute-force passwords and usernames, Malware attacks, Spoofing, and Man-in-the-Middle Attack. The attack scenarios also show various scanning mechanisms and the impact of Insider Threats on the entire network. |
format | Online Article Text |
id | pubmed-9720441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97204412022-12-06 Cyber attack evaluation dataset for deep packet inspection and analysis Shandilya, Shishir Kumar Ganguli, Chirag Izonin, Ivan Nagar, Prof. Atulya Kumar Data Brief Data Article To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cyber attacks to enable experimentation on challenges based on implementing defense mechanisms on a larger scale. For collecting the data, we captured the network traffic of configured virtual machines using Wireshark and tcpdump. To analyze the impact of several cyber attack scenarios, this dataset presents a set of ten computers connected to Router1 on VLAN1 in a Docker Bridge network, that try and exploit each other. It includes browsing the web and downloading foreign packages including malicious ones. Also, services like File Transfer Protocol (FTP) and Secure Shell (SSH) were exploited using several attack mechanisms. The presented dataset shows the importance of updating and patching systems to protect themselves to a greater extent, by following attack tactics on older versions of packages as compared to the newer and updated ones. This dataset also includes an Apache Server hosted on a different subset of VLAN2 which is connected to the VLAN1 to demonstrate isolation and cross- VLAN communication. The services on this web server were also exploited by the previously stated ten computers. The attack types include Distributed Denial of Service, SQL Injection, Account Takeover, Service Exploitation (SSH, FTP), DNS and ARP Spoofing, Scanning and Firewall Searching and Indexing (using Nmap), Hammering the services to brute-force passwords and usernames, Malware attacks, Spoofing, and Man-in-the-Middle Attack. The attack scenarios also show various scanning mechanisms and the impact of Insider Threats on the entire network. Elsevier 2022-11-24 /pmc/articles/PMC9720441/ /pubmed/36478690 http://dx.doi.org/10.1016/j.dib.2022.108771 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Shandilya, Shishir Kumar Ganguli, Chirag Izonin, Ivan Nagar, Prof. Atulya Kumar Cyber attack evaluation dataset for deep packet inspection and analysis |
title | Cyber attack evaluation dataset for deep packet inspection and analysis |
title_full | Cyber attack evaluation dataset for deep packet inspection and analysis |
title_fullStr | Cyber attack evaluation dataset for deep packet inspection and analysis |
title_full_unstemmed | Cyber attack evaluation dataset for deep packet inspection and analysis |
title_short | Cyber attack evaluation dataset for deep packet inspection and analysis |
title_sort | cyber attack evaluation dataset for deep packet inspection and analysis |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720441/ https://www.ncbi.nlm.nih.gov/pubmed/36478690 http://dx.doi.org/10.1016/j.dib.2022.108771 |
work_keys_str_mv | AT shandilyashishirkumar cyberattackevaluationdatasetfordeeppacketinspectionandanalysis AT gangulichirag cyberattackevaluationdatasetfordeeppacketinspectionandanalysis AT izoninivan cyberattackevaluationdatasetfordeeppacketinspectionandanalysis AT nagarprofatulyakumar cyberattackevaluationdatasetfordeeppacketinspectionandanalysis |