Forty-seven percent of the security professionals surveyed confessed to being “very worried” about insider threats. In addition, 14 percent of respondents revealed they do not have a security solution in place to detect insider threats. “As we’ve seen in past high-profile cases, data breaches caused by careless, malicious or compromised insiders are real and serious,” said Terry Ray, CTO at Imperva. “Because the problem begins with users that have legitimate access to enterprise data, attacks from the inside can be present for long periods of time before finally being detected. What’s more, costs associated with loss of data can run in the millions and lead to customer loss, brand damage and stock price decline.”
While there are specific strategies and tools to help manage and investigate insider threats, our respondents found them to be labor intensive. For example:
- Fifty-five percent of respondents said that managing too many security alerts was the most time-consuming element of investigating insider threats.
- Forty-four percent of respondents admitted they do not have enough staff resources to analyse data permissions correctly.
There was a silver lining as 65 percent of the security professionals surveyed estimated that machine learning-based solutions that identify insider threats would free up more than 12 staff hours a week. “To mitigate the risk, organisations should ask themselves where their sensitive data lies and invest in protecting it. Businesses can employ solutions, especially those based on machine learning technology that can process and analyse vast amounts of data, to help them pinpoint critical anomalies that indicate misuse of enterprise data and that also help them to quickly quarantine risky users to prevent and contain data breaches proactively,” Ray concluded.
