How Artificial Intelligence and Machine Learning Improve Cybersecurity
The International Telecommunication Union (ITU) is organizing an open workshop on Artificial Intelligence, Machine Learning, and Security to be held on 21 January 2019 in ITU Headquarters in Geneva, Switzerland.
The workshop will be held one day before the meeting of ITU-T Study Group 17 on Security that will take place on 22-30 January 2019 in the same venue.
According to ITU, Artificial Intelligence (AI) and Machine Learning (ML) technologies are advancing at a remarkable speed and lead to many widely beneficial applications, ranging from machine translation to medical image analysis.
AI and ML have the potential to improve cybersecurity in such a way that human analysts will become more effective and accurate in their detection of security threats and related decision-making.
Diversified data is key to data analytics. However, the volume of available data has grown so large that the number of skilled security analyst are overloaded in identifying potential attacks – the opportunity to leverage AI and ML in security is very clear.
AI empowered applications and services have been developed to focus on potential and efficiency in constrained environments, without always considering and protecting against the emergence of new security vulnerabilities, threats or other unintended consequences. If AI and ML are to be part of security defences, there is a need to explore how these defences might be subverted.
Several of the threats (e.g. automated spear phishing, personalised propaganda) rely on attackers gaining access to personal information about individuals. The risks posed by AI and ML to security and privacy should be mitigated, which includes threat-detection methods that misclassify malicious threats as benign, automated systems that fail to detect key stimuli, or authentication mechanisms capable of misidentification.
The workshop will focus on addressing three critical aspects: what is the relationship between AI/ML and security; how AI and ML can be utilized to improve the cyber defence capability; and which risks should be addressed to build on AI and ML empowered applications, especially privacy risks.