Alejandro Mosquera López is an online safety expert and Kaggle Grandmaster working in cybersecurity. His main research interests are Trustworthy AI and NLP. ORCID iD icon

Thursday, March 17, 2022

Defending and attacking ML Malware Classifiers for Fun and Profit: 2x prize winner at MLSEC-2021

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 exercise their security and machine learning skills under a plausible threat model: evading antimalware and anti-phishing filters. In the competition, defenders aimed to detect evasive submissions by using machine learning (ML), and attackers attempted to circumvent those detections.

Towards Machines that Capture and Reason with Science Knowledge

 In 2015 I took part on a machine learning competition hosted on Kaggle aiming to solve a multiple-question 8th grade science test. At that time there weren't large pretrained models to leverage and (unsurprisingly) best performing models were IR-based that would barely achieve a GPA of 1.0 in the US grading system: