The University of Texas at San Antonio (UTSA) is proving its worth as a pioneer in cyber security after being awarded top honours in an international cyber security competition.
The competition known as the AICS 2019 challenge is run and funded by MIT Lincoln Laboratory. It rewarded the university for its solution to detect malware using AI (artificial intelligence).
The initial challenge asked researchers around the world to create a mechanism for classifying a number of highly dangerous malware bugs which have evolved to continually confound IT infrastructures to lie undetected within systems for decades.
The task was made all the trickier because MIT Lincoln Laboratory ensured “white hat” (ethical) hackers could access a limited training data set “with an unbalanced number of malwares”. Each team involved was given just one week to put together a real-world solution after being given access to the MIT test information.
The international team behind the prize-winning solution was led by Shouhuai Xu, director of UTSA’s Laboratory for Cybersecurity Dynamics and professor in the UTSA Department of Computer Science.
“The challenge is as realistic as what a cyber defender would encounter in the wild, because little information about the ‘attacks’ is given to us. This exercise mimics what happens in the real world.”
Despite the many millions poured into combatting malware, it is considered one of the primary dangers to cyber defences around the world with nearly 670 million varieties swirling around the web. Even more concerning is the fact that undetected malware operation rates on computers has doubled over the past four years.
The alarming nature of malware within the broader cyber landscape was also touched upon by Xu.
“There is an urgency in solving the problem because computer malware writers are getting increasingly crafty so as to evade any existing detection system. This is the reason the AICS Challenge exists—to find prototypes for real world solutions.”
The initial data set provided by MIT Lincoln Laboratory was downloaded by over 300 applicants, in an event that has been held for the past three years.
“This is the first time we’ve focused on adversarial learning and it’s been the most successful,” said William Strelein, Chair of the AICS Challenge and Group Leader of Cyber Analytics and Decision Systems – Group 58 at the MIT Lincoln Laboratory.
“Xu had the highest score in the challenge and a proposal that would serve as a really good paper,” Streilein said.
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