Machine Learning: ESET thoroughly analyzes the role of Artificial Intelligence in view of the Mobile World Congress 2019. According to a relevant survey of the company, 80% of the participants believe that AI and Machine Learning technologies will help fight cyber threats
The debate over Artificial Intelligence (AI) has taken on great proportions nowadays. The idea of an everyday life full of smart machines seems real through the images created by marketing, but in reality we are still very far from such a scenario. 
In this context, in recent months ESET researchers have been diligently investigating the role of AI (Machine Learning - ML) in combating cyber threats.
The results of this ESET survey were collected in a comprehensive report entitled “Machine-Learning Era in Cybersecurity: A Step Towards a Safer World or the Brink of Chaos?”, which was recently made public on the occasion of the Mobile World Congress.
In mid-2018, ESET commissioned denergy of this research with the aim of examining what are the basic beliefs regarding this particular technology. 82% of respondents believe that their organization has already deployed a cybersecurity solution that leverages ML technology, while only 23% said they do not plan to deploy an ML-based cybersecurity solution in the near future.
Perhaps more importantly, 80% also believe that ML already helps or will help their organization detect and respond to threats faster, while 76% of respondents somewhat or strongly agree that this technology will provide solutions to problem lack of cybersecurity skills in the work environment.
ESET has over 30 years of experience specializing in cybersecurity and has focused on machine learning applications for more than 20 years. Based on this experience, its experts have developed a powerful, durable and innovative machine learning technology.
“ESET has built its own machine learning technology into the cloud system ESET LiveGrid®, which examines the "reputation" of the object, i.e. whether the specific object has been flagged as malicious at some other time. Thanks to this integration, our customers, from simple home users to enterprises of all sizes, enjoy the benefits of ML technology.
Especially for large-sized enterprises, an even higher level of protection is achieved with ESET Dynamic Threat Defense, a cloud-based sandboxing solution to detect new, previously unknown threats" comments Juraj Jánošík, ESET Researcher and AI expert.
He adds that, although many areas of human activity have already undergone transformational changes thanks to Machine Learning, the greater and greater changes that machine learning we have not experienced them yet.
Machine Learning-based technologies will increasingly help combat it cyber fraud, in the evaluation and optimization of processes, in the improvement of control procedures and in the development of new solutions to existing problems.
However, as with most innovations, machine learning has its drawbacks.
"As business, infrastructure and our personal lives increasingly enter the realm of digital technology, new risks are emerging. Cybercriminals can use Machine Learning in a number of ways: to power their malware, target specific victims and extract valuable data, target zero-day vulnerabilities, or protect compromised systems such as botnets", Says Jánošík.
The publication of the research coincides with the holding of the Mobile World Congress in Barcelona. Juraj Jánošík, one of the authors of the relevant white paper, will be at the ESET stand (Hall 7, stand 7H41). THE ESET will continue to explore Machine Learning and Artificial Intelligence, presenting new research and important findings on mobile security - specifically for cyber threats on the Android platform - during the Mobile World Congress (MWC), held on 25- February 28, 2019 in Barcelona.
Those interested in learning more about the role of ML in cyber security, e.g. for the misuse of machine learning by cybercriminals to translate spam emails and make them look more trustworthy, or to improve targeting of victims, for its possible misuse to improve malware in the future, and for the limitations of technology, read the report at WeLiveSecurity.com (PDF).
