Ai and Security Resources

Posted: February 20, 2018 by James Pavur

I recently gave a presentation at Rhodes House regarding the intersections between AI and cybersecurity. These are some articles, code samples, tools, etc. that I either referenced in the presentation or are related to what we discussed. Hopefully it’s useful both to those of you who were at the presentation and to anyone looking for a decent collection of resources about the relationship between AI and cybersecurity.

Resources from the Presentation

All jupyter notebooks (you can run these in google colab)

DARPA Cyber Grand Challenge

Main DARPA Event Site:

DARPA Youtube Playlist:


Github Repository: DEFCON Presentation:


Github Repository: Academic Paper:

Imagenet Database

Bad Flamingo

Github Repository:

Hack Cambridge Submission:

Real World 3D Adversarials

Blog Post:

Academic Paper:

Cracking Captchas


Related Neural Network Walkthrough:

Tay AI

Telegraph Write Up:

Microsoft Official Statement:

Various Other References and Examples


Cleverhans - Adversarial & Defense Toolkit:


Useful Intro to Adversarial Examples:

Discussion of Defending Against Adversarials:


N. Papernot, P. McDaniel, S. Jha, M. Fredrikson, Z. B. Celik and A. Swami, “The Limitations of Deep Learning in Adversarial Settings,” 2016 IEEE European Symposium on Security and Privacy (EuroS&P), Saarbrucken, 2016, pp. 372-387. doi: 10.1109/EuroSP.2016.36

Papernot, Nicolas, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik, and Ananthram Swami. 2017. “Practical Black-Box Attacks Against Machine Learning.” In Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, 506–519. ASIA CCS ’17. New York, NY, USA: ACM.

J. Sahs and L. Khan, “A Machine Learning Approach to Android Malware Detection,” 2012 European Intelligence and Security Informatics Conference, Odense, 2012, pp. 141-147. doi: 10.1109/EISIC.2012.34