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Welcome to Chalkboard Wisdom
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Synthetic for Cybersecurity
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Solve a Problem Make your own Cyber Synth Data CSE-CIC-IDS2018 dataset source + sample
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Make your own Cyber Synth Data CSE-CIC-IDS2018 dataset source + sample

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Using the CSE-CIC-IDS2018 dataset source or others like it, you can see and practice on creating synthetic data to augment Network Logs or other cybersecurity data.

Communications Security Establishment (CSE) and The Canadian Institute for Cybersecurity (CIC) that use the notion of profiles to generate cybersecurity dataset in a systematic manner. It incluides a detailed description of intrusions along with abstract distribution models for applications, protocols, or lower level network entities. The dataset includes seven different attack scenarios, namely Brute-force, Heartbleed, Botnet, DoS, DDoS, Web attacks, and infiltration of the network from inside. The attacking infrastructure includes 50 machines and the victim organization has 5 departments includes 420 PCs and 30 servers. This dataset includes the network traffic and log files of each machine from the victim side, along with 80 network traffic features extracted from captured traffic using CICFlowMeter-V3.

For more information on the creation of this dataset, see this paper by researchers at the Canadian Institute for Cybersecurity (CIC) and the University of New Brunswick (UNB): [Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization](http://www.scitepress.org/Papers/2018/66398/66398.pdf).

Get it now!

Using the CSE-CIC-IDS2018 dataset source or others like it, you can see and practice on creating synthetic data to augment Network Logs or other cybersecurity data.

Communications Security Establishment (CSE) and The Canadian Institute for Cybersecurity (CIC) that use the notion of profiles to generate cybersecurity dataset in a systematic manner. It incluides a detailed description of intrusions along with abstract distribution models for applications, protocols, or lower level network entities. The dataset includes seven different attack scenarios, namely Brute-force, Heartbleed, Botnet, DoS, DDoS, Web attacks, and infiltration of the network from inside. The attacking infrastructure includes 50 machines and the victim organization has 5 departments includes 420 PCs and 30 servers. This dataset includes the network traffic and log files of each machine from the victim side, along with 80 network traffic features extracted from captured traffic using CICFlowMeter-V3.

For more information on the creation of this dataset, see this paper by researchers at the Canadian Institute for Cybersecurity (CIC) and the University of New Brunswick (UNB): [Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization](http://www.scitepress.org/Papers/2018/66398/66398.pdf).

Using the CSE-CIC-IDS2018 dataset source or others like it, you can see and practice on creating synthetic data to augment Network Logs or other cybersecurity data.

Communications Security Establishment (CSE) and The Canadian Institute for Cybersecurity (CIC) that use the notion of profiles to generate cybersecurity dataset in a systematic manner. It incluides a detailed description of intrusions along with abstract distribution models for applications, protocols, or lower level network entities. The dataset includes seven different attack scenarios, namely Brute-force, Heartbleed, Botnet, DoS, DDoS, Web attacks, and infiltration of the network from inside. The attacking infrastructure includes 50 machines and the victim organization has 5 departments includes 420 PCs and 30 servers. This dataset includes the network traffic and log files of each machine from the victim side, along with 80 network traffic features extracted from captured traffic using CICFlowMeter-V3.

For more information on the creation of this dataset, see this paper by researchers at the Canadian Institute for Cybersecurity (CIC) and the University of New Brunswick (UNB): [Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization](http://www.scitepress.org/Papers/2018/66398/66398.pdf).

The Forever Scroll of Thank You's: Webalon.com | Harzing.com | arxiv.org/ | openrefine.org | OpenAI | Semantic Scholar | Google Scholar | Pubmed | Tableau | Turing Institute | msp.org | TowardsDataScience | Medium.com | GitHub | And so many more who will continue to make this project possible! :)

The Forever Scroll of Thank You's: Webalon.com | Harzing.com | arxiv.org/ | openrefine.org | OpenAI | Semantic Scholar | Google Scholar | Pubmed | Tableau | Turing Institute | msp.org | TowardsDataScience | Medium.com | GitHub | And so many more who will continue to make this project possible! :) The Forever Scroll of Thank You's: Webalon.com | Harzing.com | arxiv.org/ | openrefine.org | OpenAI | Semantic Scholar | Google Scholar | Pubmed | Tableau | Turing Institute | msp.org | TowardsDataScience | Medium.com | GitHub | And so many more who will continue to make this project possible! :)

Thank you notes:

arXiv - https://arxiv.org/ - The most amazing site for math and science papers on the subject of synthetic data

Search Engines that Soar - Semantic Scholar, Google Scholar, PubMed

Community Forums: Towards Data Science, Medium, GitHub, StackExchange

OpenAI and ChatGPT. DALL-E created my product images. I found Tiki Toki using ChatGPT, and it guided my ideation to structure in the timeline!

YouTubers to Love - StatQuest, 3Blue1Brown, Machine Learning TV, Jordan Harrod, Normalized Nerd, StudyTube, Jeffrey Lush, and so many more!!

Tools and Software Utilized

Publish or Perish - Download to your system and get citations lists from search engines! - https://harzing.com › resources › publish-or-perish

Google OpenRefine - https://openrefine.org/

Tiki Toki: Special thanks to http://www.webalon.com/ for the Timeline software tool

Relevant Publication Repositories

Nonprofit Publishing, by Mathematicians, for Mathematicians. - https://msp.org/

arXiv open-access archive for 2 million+ papers - https://arxiv.org/

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