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Predictive risk technology helps fight phishing

Phishing attacks are on the increase and are becoming increasingly sophisticated. This means that older technologies such as blacklisting known phishing sites are struggling to keep up with the threat. The Anti Phishing Working Group detected a 250 percent jump in phishing sites between October 2015 and March 2016.

Fraud protection company Easy Solutions is helping to combat the problem with the public beta launch of its Swordphish predictive phishing and malware risk assessment technology.

Swordphish is an API-based tool that helps organizations use the power of prediction to combat ‘alert fatigue’ and to detect phishing, malware and ransomware attacks in the critical period before these threats are added to conventional blacklist-based solutions, filling a gap in current detection systems. It uses three separate machine-learning classifiers that have been trained to recognize subtle and discrete differences between benign URLs and the malicious ones used by cybercriminals, malware authors and fraudsters.

“We developed Swordphish as an internal tool to enhance our ability to detect and prioritize truly critical attacks within a sea of streaming security event data,” says Daniel Ingevaldson, CTO of Easy Solutions. “Once we saw the power of Swordphish, we decided to make the technology available publically to support our customer’s requirements for predictive malware detection, predictive spear-phishing detection, improved security event processing efficiency and orchestration. We are excited to be accepting requests to access the Swordphish technology and we look forward to working with our customers to deploy Swordphish to decrease response time, gain insight into zero-day attacks and to help reduce the cost and complexity of managing large security volumes”.

For more information and to apply to join the beta program you can visit the Easy Solutions website.

Image Credit: Maksim Kabakou / Shutterstock

Source:

http://betanews.com/2016/08/11/predictive-risk-fight-phishing/

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