Hackathon is over: Here are our winners!

A few weeks ago Wallarm has launched a hackathon to create a machine learning / AI model to detect attacks among normal web requests. The competition was run on Kaggle as InClass. In this competition, Kagglers were asked to develop models that identify injections among neutral input vectors using...

TensorFlow Dataset API for increasing training speed of neural networks

by M.Salnikov, Wallarm Research Wallarm AI engine is the heart of our security solution. Two key parameters of our AI engine efficiency are how fast neural networks can be train to reflect the updated training sets and how much compute power need to be dedicated to the training on the on-going...

Adversarial Robustness Toolbox: ART

The Adversarial Robustness Toolbox ART, an open source software library, supports both researchers and developers in defending deep neural networks against adversarial attacks, making AI systems more secure. Its purpose is to allow rapid crafting and analysis of attack and defense methods for...

The First Step-by-Step Guide for Implementing Neural Architecture Search with Reinforcement…

The First Step-by-Step Guide for Implementing Neural Architecture Search with Reinforcement Learning Using TensorFlow Our team is no stranger to various flavors of AI including deep learning DL. That’s why we’ve immediately noticed when Google came out with AutoML project, designed to make AI bui...

Detects Clickbait Headlines Using Deep Learning: Clickbait Detector

Detects Clickbait Headlines Using Deep Learning People continually fall for clickbait and as Wired in it’s article mentioned Whether you think clickbait is on the rise, obscurant and self-negating, not such a big deal, or the root of all evil, one thing is clear about it: It’s increasingly hard t...

deep-pwning - Metasploit for Machine Learning

Deep-pwning is a lightweight framework for experimenting with machine learning models with the goal of evaluating their robustness against a motivated adversary. Note that deep-pwning in its current state is no where close to maturity or completion. It is meant to be experimented with, expanded...

Relational Learning Tutorial

At FireEye, we apply machine learning techniques to a variety of security problems. Malware detection and categorization is a great use of the technology, and we believe that it can also play a role in security challenges that extend beyond malware. In one such R&D effort, the Innovation & Custom...