AI in your Email: What is Human Layer Security?

How is your organization addressing insider threats caused by misrouted email?

A UK study released in CISO Magazine in December 2019 revealed that, “44 percent of employees admit that they’ve mistakenly exposed personally identifiable information (PII) or business-sensitive information using their corporate email accounts. Over 70 percent of respondents have experienced this type of breach during the last five years. …”

Another study from 2018 suggested that 88% of data breaches are caused by human factors and only 12% by malicious attacks. In that study, “The most common error was to send sensitive data to the wrong recipient, which was the cause of 37% of reported data breaches.”

While clicking on links that may bring malicious malware has received the majority of email security attention over the past year, especially during this current pandemic, various responses to phishing have also received the greatest level of investment from technology and security industry leaders who address email threats.

But what can be done to better protect sensitive information sent from public and private sector inboxes? Can AI help?   

Allow me to introduce you to a new security industry category called “human layer security” with cutting edge AI solutions to address these email routing problems. But before I bring in the top industry expert that I could find on human layer security, I want to emphasize that we are NOT addressing security awareness training programs – which my readers know I like to write about. No, this is technology that works with MS Outlook or other email.  

To understand the differences and how they work together – please read my interview below.

Introducing Tony Pepper

Recently, I had the distinct pleasure to meet a global security industry leader who really impressed me with his knowledge, passion and stories told (Read more...)

*** This is a Security Bloggers Network syndicated blog from Lohrmann on Cybersecurity authored by Lohrmann on Cybersecurity. Read the original post at: