Recent peer-reviewed studies by artificial-intelligence powered cybersecurity startup CYR3CON show how patterns in hacker conversations can predict enterprise cyberattacks.
TEMPE, Ariz. (PRWEB) November 05, 2018
Recent peer-reviewed studies by artificial-intelligence powered cybersecurity startup CYR3CON show how patterns in hacker conversations can predict enterprise cyberattacks. The pair of studies and associated provisional patents describe DarkMention and highlight several use cases including the prevention of attacks against various cryptocurrencies and their exchanges.
“Today’s applications of artificial intelligence to cybersecurity tend to focus on identifying if either an attack occurred or if someone is currently attempting an attack,” stated CYR3CON CEO Paulo Shakarian, “but hackers are people too, and they need to prepare for attacks – which presents us with an opportunity to better predict their actions.”
CYR3CON turned to the darkweb – a shadowy part of the Internet where malicious hackers, among other criminals, prepare, develop and conduct their illicit activities. “While hackers typically do not discuss specific targets,” explains Shakarian, “there are definite patterns in conversations that we uncover prior to an attack.” However, finding these patterns is no small task – darkweb hacker discussions are inherently “messy” data to deal with. The company also notes that simple keyword searches alone do not provide very predictive attack indicators. “We found if you rely on darkweb discussions around certain key terms you end up with a lot of false positives and that false positive rate leads to intense manual effort. We use artificial intelligence to cut a lot of that out,” Shakarian explained further.
The studies show not only the application of DarkMention to the enterprise but also how it can be used to predict attacks targeting cryptocurrencies. The papers will be presented at the IEEE conference for Intelligence and Security Informatics held Nov. 8-10 in Miami, Florida.
Originally funded by the Intelligence Advanced Research Projects Activity (IARPA) Cyberattack Automate Unconventional Sensor Environment (CAUSE) Program, the company earned recognition for predictions concerning several major attacks. In October the company announced the completion of a venture-backed fundraising round.
CYR3CON combines machine learning and data mined from hacker communities (i.e. darkweb, deepweb) to predict cyberattacks. The platform-based solution allows for use cases such as attack prediction and vulnerability prioritization. This provides corporate security professionals the means to take early action and avoid cyber-attacks.
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