Machine Learning Brings Many Benefits… But Also Many Risks to Your Clients.

Cybersecurity and artificial intelligence (AI) used to be viewed as separate innovations in technology. Today, cybersecurity and AI go hand-in-hand as experts use machine learning to develop advanced security methods. But cyber criminals are using machine learning too, and they’re innovating faster than security experts can keep up.

Cyber criminals have developed machine learning enabled attacks and are beginning to leverage them against businesses. This has major implications for all industries as attacks become more sophisticated and ultimately more successful. Learn what this means for you and your clients—and what the experts ProWriters recommend to stop it.

What Are Machine Learning Enabled Attacks?

Machine learning refers to the ability for computers to learn, adapt, and respond without being specifically programmed to execute certain tasks. Machine learning enabled attacks happen when cyber criminals use this artificial intelligence technology to carry out a cyber attack.

Using machine learning, hackers can automate some or all of the data breach process, including:

• Vulnerability discovery—finding a weakness in the targeted network
  
• Initial exploitation—exploiting the weakness to gain access to the network
  
• Targeted exploitation—finding and exploiting vulnerabilities within the network
• Data theft—removing sensitive or valuable data from the network

What Are the Implications of Machine Learning Enabled Attacks?

Automated cyber attacks have major implications for data security.

One implication is that hackers can step up the number of attacks they carry out. According to a recent report by Cybersecurity Ventures, the number of cyber attacks against businesses is expected to rise to one every 14 seconds by 2019. The number of businesses targeted by cyber attacks is expected to grow as hackers use machine learning to carry out a greater number of attacks with a higher rate of success.

Phishing attacks are also expected to become more sophisticated. It will become harder to determine legitimate emails from malicious ones. This is because computer programs can learn enough about you to accurately imitate a trusted personal source. Phishing emails using machine learning can impersonate a boss, coworker, friend, or reputable organization with increasing precision. And because 91% of data breaches already start with a phishing email, this will be an area to watch as hackers use machine learning to innovate these attacks.

The implications are also bad for small businesses, as cyber criminals are automating attacks against them at an increased rate. With the advent of machine learning enabled attacks, small and medium-sized businesses are now the preferred target for hackers. This is because small and medium-sized businesses are seen as less secure and easier to exploit with mass automation and machine learning.

What Can You Do to Protect Against Machine Learning Enabled Attacks?

The implications for criminal activity with machine learning may seem bleak. But luckily, there are steps you and your clients can take to protect against these attacks.

1. Keep software up to date
   Outdated software is particularly vulnerable to cyber attacks, as hackers will exploit weaknesses in software as soon as they learn about them. To combat this, developers will release patches to fix vulnerabilities as they are discovered. It is crucial to update and patch software before hackers have the chance to use the vulnerability to launch an attack. There are several examples of companies being attacked because they didn’t patch their software in time.
2. Strengthen all credentials
   Use complex passwords that don’t use easy-to-guess personal information. Be sure to change your passwords approximately every 90 days. You can refer to guidelines from the United States Computer Emergency Readiness Team (U.S.-CERT) for password best practices.
3. Use multifactor authentication
   Going beyond a simple username and password makes it harder for cyber criminals to use machine learning to break into your network. Enhance your cyber security with multi-factor authentication, which adds an extra step to accessing your information by requiring an additional piece of information only you would know.
4. Protect yourself with cyber liability insurance
   Machine learning enabled attacks can cause serious damage to an organization. General liability policies don’t cover the first and third party costs associated with a breach, such as notification costs, forensic IT costs, and fines and penalties. Cyber liability insurance today is more comprehensive than ever and is optimized to protect against these sophisticated data breaches.

Even though there’s a lot of good that comes with machine learning, it’s important to be aware of the dangers it can bring. To learn more about how to make sure you and your clients are protected, download our FREE ebook, Creating a Comprehensive Cyber Security Risk Management Plan, or speak with an expert from ProWriters today.