Incredible software can detect Cyberattack with high efficiency
Can you imagine if we could predict when a cyberattack is going to occur before it actually happens, and prevent it? Wouldn’t it be a revolutionary idea for Internet Security?
Security researchers at MIT have developed a new Artificial Intelligence-based cyber security platform called ‘AI2’, which has the ability to predict, detect, and stop 85% of Cyber Attacks with high accuracy.
Cyber security is a major challenge in today's world as government agencies, corporations, and individuals have increasingly become victims of cyberattacks. The attacks are rapidly finding new ways to threaten the Internet that consequently, has become extremely difficult for the good guys to keep up with them.
A group of researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) are working with the machine-learning startup Pattern-Ex to develop a line of defense against such cyber threats.
The team has already developed an Artificial Intelligence system that can detect 85 percent of attacks by reviewing data from more than 3.6 Billion lines of log files each day and informs anything suspicious.
The new system does not just rely on the artificial intelligence (AI), but also on human input, which researchers call Analyst Intuition (AI). That is why it has been given the name of Artificial Intelligence Squared or AI2.
How Does AI2 Work?
The system first scans the content with unsupervised machine-learning techniques, and subsequently presents its findings to human analysts at the end of each day.
The human analyst then identifies which events are actual cyberattacks and which aren't. This feedback is then incorporated into the machine learning system of AI2, and is used the next day for analyzing new logs.
It's simple:
"The more data it analyzes, the more accurate it becomes."
In its test, the team demonstrated that AI2 is roughly 3 times better than similar automated cyberattack detection systems used today. AI2 also reduces the number of false positives by a factor of five.
According to Nitesh Chawla, computer science professor at Notre Dame University, AI2, "continuously generates new models that it can refine in as little as a few hours, meaning it can improve its detection rates significantly and rapidly. The more attacks the system detects, the more analyst feedback it receives, which, in turn, improves the accuracy of future predictions – that human-machine interaction creates a beautiful, cascading effect."
The team presented their work last week at the IEEE International Conference on Big Data Security in New York City.
This is breaking news to fight the increasing field. Ultimately, let us see how AI2 helps to create the Internet a safer place, and how long it will take for AI2 be implemented into large-scale security platforms in the near future.
Source: Swati Khandelwal
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