MLSEC (Machine Learning Security Evasion Competition) is an initiative sponsored by Microsoft and partners CUJO AI, NVIDIA, VMRay, and MRG Effitas with the purpose of raising awareness of the expanding attack surface which is now also affecting AI-powered systems. In its 3rd edition the competition allowed defenders and attackers to…

In 2015, Microsoft provided the data science community with an unprecedented malware dataset and encouraging open-source progress on effective techniques for grouping variants of malware files into their respective families. …

Abstract Adversarial training can provide neural networks with significantly improved resistance to adversarial attacks, thus improving model robustness. However, a major drawback of many existing adversarial training workflows is the computational cost and extra processing time when using data augmentation techniques. This post explores the application of embedding perturbations via the…

Introduction Malicious actors can alter the expected behavior of a neural network in order to respond to data containing certain triggers only known to the attacker, without disrupting model performance when presented with normal inputs. An adversary will commonly force these misclassifications by either performing trigger injection [19] or dataset poisoning…