January 21, 2019

AI and machine learning are the latest tools being used by businesses to stop cyber attacks and prevent cybercrime. However, what if this employee computer monitoring tool can be used to stop insider threats such as misusing company data or employees leaking important information?

Based on one study, the health and pharmaceutical section is the largest target of criminals internationally. The amount of damages that are created through intellectual property theft has to lead to billions of dollars lost each year.

Even large organizations that have thousands of employees has suffered from inaction. For instance, Merck, one of the largest pharmaceutical companies in the U.S, has lost over a hundred millions dollars by the end of the year.

At the same time, the situation isn’t as black and white as it first appears. While there are people outside of your organization that will want to harm you, the real threat you need to be focusing on is the one you’d least expect:

The one that’s currently in your business.

Breaking Down Insider Threats

External threats within the pharma and biotech business get more attention because they are more visible. Then, it becomes a fight between good vs. evil. What executives don’t understand is that the reason why external threats are more successful is that they utilized an insider.

Insider threats come in two different forms: employees who made a mistake and an employee who has malicious intentions. About 75% of those insider threats were caused by insider threat. However, the number over 80% are made due to human error instead of rogue agents.

In pharmaceuticals and biotechnology, insider threats present an economic and a public health issue. Whether its intentionally or unintentionally, these actors made it difficult for companies to maintain their competitiveness within the industry – which also is a risk to potential patients as well.

How AI and Machine Learning Can Help

Many companies assume that because they run rigorous background checks, and somewhat ethical employees, ‘insider’ threats aren’t applied to them. Data exfiltration occurs when an innocent person (i.e., employee) is targeted (usually through phishing attacks) at times when they’ve accidentally opened the company to risk.

With machine learning, you can get assistance with fast forensics when a problem occurs, and call out specific behavioral issues that are able to be corrected during the future.

Also, you can create a user behavior analytics to help spot the problematic employee. UBA tools work by examining patterns of multiple user activity while using machine learning to find suspicious behavior that might indicate a threat.

This technology can alert you about who is violating your company’s policies. This includes logging in at suspicious times or multiple login attempts. Machine learning helps with identifying potential data leaks and know what user is responsible for the crime.

Conclusion

Through AI and machine learning, people will know what user caused the problem and know what problems were committed. After that, simply use an IGI Solution to auto-suspend the account. Conclusively, stay proactive to ensure that your company is protected from external threats.

About the Author
Steven Sanders is a writer, and blogger . He lives in Los Angeles, California and enjoys spending time with his family and on his motorcycle when not writing. He can be reached at steven.sanders@gmail.com.