Agenda

While the idea of artificial intelligence and machine learning have been influencing various fields for decades now, their full transformative potential is yet to be realized. ML-based technologies increasingly help fight large-scale fraud, evaluate and optimize business processes, improve testing procedures and develop new solutions to existing problems. We, at ESET, recognized its potential early on and employed it to improve malware detection over 20 years ago. To this day, this symbiosis continues, various machine-learning technologies being an integral part of the ESETs protective layers. Like most innovations, however, even machine learning has drawbacks and limitations. Unfortunately, technological advances are not exclusively available to cybersecurity defenders. Cybercriminals are aware of the new prospects too and do not hesitate to utilize ML-based technologies to make their malicious code and activities more efficient. The question for the future remains, will the pros of machine learning outweigh the cons or will the technology lead to major disruption and deterioration of the cybersecurity equilibrium.

Juraj Jánošík joined ESET in 2008 as a Malware Analyst, he holds a bachelor’s degree in Applied informatics and a master’s degree in Robotics, both from the Slovak University of Technology. Currently, he is the leader of ESET's Automated Threat Detection and Machine Learning section. He was a member of several international working groups focusing on botnet eradication (e.g. Dorkbot, Gamarue, 3ve). He also presented at several international private and public conferences including RSA, MWC and CARO.