The percentage of data breaches that used web application attacks has grown rapidly. A new report recommends machine learning tech for web app security testing.
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.
