The Dilemma: It’s not if but when for a data breach. When the worst happens, it pays to have the best AI technology
When a client suffered a security incident tied to their CFO’s email which included thousands of messages and attachments that were potentially compromised, they immediately engaged the law firm Seyfarth Shaw and noted cybersecurity and digital forensics partner Richard Lutkus. Lutkus is a pioneer in law and technology with significant success in helping clients avoid or clean up costly cybersecurity incidents. He knew he needed a software solution to accurately and efficiently identify all of the compromised PI from the incident.
AI put to the test
Lutkus, who encounters companies struggling with PI identification in the data breach context daily, decided to test the industry’s leading tools for his client. The dataset consisted of 195,000 documents, mostly emails, and attachments. Lutkus ran the document set through both Text IQ’s AI solution and other leading solutions to detect PI for human assessment.
From this challenge,12,287 documents, post-deduplication, were identified as containing PI. “Text IQ’s AI was so much better at finding the true PI than the other approaches. Ultimately, we completed our review using Text IQ’s results after our sampling and evaluation,” Lutkus said.
Clearly, Text IQ’s AI solution was superior to the alternative options, but what about other providers of PI identification that utilize AI technology? In the pursuit of continuous improvement, Text IQ put the company’s AI for PI identification up against PI identification solutions from Microsoft Azure, AWS, and Google. While these cloud providers do not specialize in finding sensitive information like Text IQ, their APIs are widely available and extremely popular.
Richard Lutkus of Seyfarth assisted with this test by obtaining the client’s approval to utilize the subset of 12,287 documents that had been recently reviewed as a result of a privacy assessment following a security incident. Each of the documents in this subset had undergone both AI and human review and was known to include PI.