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Web Apps Can Be More Secure With Machine Learning

 

The cyber-security industry will grow from $102 billion in 2015 to $155 billion in 2020, with a compound annual growth rate of 52 percent, according to Frost Sullivan. But in its report, “How Machine Learning Will Strengthen the Web Application Security Testing Market,” the think tank also points to a different trend when it comes to web application attacks: Insecure web applications cause the most data breaches. Quoting Verizon’s “Data Breach Investigation Report (DBIR) for 2016,” Frost and Sullivan noted that “Although attacks on web applications account for only 8 percent of overall reported incidents (whether they were successful or not), attacks on web applications accounted for over 40 percent of incidents resulting in a data breach, and were the single-biggest source of data loss.” Furthermore, the percentage of data breaches that leveraged web application attacks increased rapidly—from 7 percent in 2015 to 40 percent in 2016. In the face of this trend, Frost and Sullivan’s report recommends machine learning technology for web application security testing.

 

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