Cyberspace is an increasingly hostile environment. In 2015, a PwC study of U.S. organizations found that 79 percent of respondents had detected a security incident during the year.
Today, malicious hackers continue to wage on business networks and systems. Their aim – to extract data to sell on the black market. Making use of the latest technology, these criminals exert huge pressure on businesses to defend its assets. As they continue to adopt rapidly advancing attack technologies, the differentiation between a malicious attacker and a genuine user is increasingly difficult to spot.
Cybersecurity experts are facing the daunting reality that they may have reached the limit of what humans can achieve in cyber defense. Thankfully, the answer to this issue may already have arrived, following in the form a platform known as AI-Squared.
Rise of the robots.
Unveiled to the world in April, AI-Squared is a collaborative project between MIT’s Computer Science and AI Laboratory (CSAIL) and a machine-learning startup known as PatternEx . Its function – to identify cyber-attacks.
The platform combines Artificial Intelligence (AI) and Analyst Intuition (AI) – hence the name AI-Squared. It works by parsing huge amounts of data – generated by users — searching for odd activity using a recurrent neural network in combination with machine learning techniques. This is a process known as unsupervised learning, and it’s used to find anomalies – the proverbial needles in the haystack.
Once identified, the platform notifies a human analyst, presenting its findings. The human analyst then confirms whether the user activity is an attack or a genuine visitor, which is relayed back to the AI. The AI turns these decisions into a model for use the next day. This is a process known as supervised learning.
It was announced that the platform is now capable of detecting 85 percent of cyberattacks.