Presented by Tessian

Traditional machine learning methods simply aren’t equipped to account for the complexities of human relationships. Learn how to protect your data with a new kind of machine learning and a people-centric approach to cybersecurity when you join this VB Live event!

Register for free right here. 

From misdirected emails to accidental clicks of a mouse, a vast number of data breaches are caused by human error. Every day employees access the a company’s data, often sharing it across their company and with outside contacts.

In a perfect world, cyber security training and company policies would ensure that data was always secure. But humans make mistakes, break the rules, and are easily hacked. A single slip or phishing attack can result in a major data breach — the kind that traditional cybersecurity methods just can’t predict or prevent.

VB TRansform 2020: The AI event for business leaders. San Francisco July 15 - 16

That’s because while the machine layer can be secured with any one of the cyber security products crowding the market, the complexities of human behavior make securing the human layer significantly more challenging, because humans are simply unpredictable.

An employee might not recognize, for instance, that sending work documents to their personal email account carries a tremendous amount of risk. A single typo could mean a misdirected email sent to the wrong address, and the consequences could be dire, from penalties and fines to regulatory bodies and bad publicity resulting in loss of reputation to the company.

And then some employees with access to valuable company data might be tempted to cash in, such as the recent case where an employee sold 68,000 customer records to scammers.

Sometimes the human risk comes from outside the company, such as hackers targeting employees with spear phishing attacks which impersonate internal and external contacts. Employees are always vulnerable to cybercriminals, and bad actors are always hunting for ways to gain access to company networks.

In the end, the problem is that human behavior simply can’t be codified with the “if-this-then-that” logic that powers traditional machine learning, and those algorithms are at a loss when it comes to predicting a potential threat. We all communicate differently, we use natural language, and our behaviors and relationships are never static, but change over time as we make new connections, take on new projects, and respond to an ever-changing work environment.

Cyber security training and company policies are essential tools to help minimize threats and ensure your people are keeping themselves safe, but businesses need a more robust, people-centric approach to cybersecurity for those moments when inevitable errors occur. They need advanced technologies that understand how individuals’ relationships and behaviors change over time in order to effectively detect and prevent threats caused by human error.

Human layer security is the answer, taking on the challenge of protecting your most important asset — your people. Human layer security (HLS) is designed to secure human-digital interactions in the workplace. It works together with your machine layer security, which protects networks, devices, and apps, to protect your employees, contractors, customers, and suppliers.

It uses a different type of machine learning: stateful machine learning.

Stateful machine learning essentially understands human behavior and relationships, enabling it to detect and prevent dangerous activity in real time to protect employees from making errors. It can even learn and adapt to how people work without getting in the way or impeding productivity. Stateful machine learning models analyze historical email data in order to understand human relationships and communication patterns.

Once you know what “normal” looks like, stateful machine learning can automatically predict and prevent dangerous email activity, without disrupting employees and automatically prevent the most advanced forms of spear phishing, accidental data loss, and data exfiltration in real time.

To learn more about the benefits of human layer security, how stateful machine learning can transform your cybersecurity setup and protect your people, and more, register now for this VB Live event.

Don’t miss out!

Register here for free.

Attendees will learn:

  • How stateful machine learning can accurately predict behaviors and detect possible human-made threats before they do damage
  • How technology can prevent data breaches caused by people making mistakes, breaking rules or being hacked
  • How to empower employees to correct damaging mistakes before they make them


  • Ed Bishop, Co-founder and Chief Technology Officer, Tessian

More speakers coming soon!