Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we cover how machine learning can be applied in the cybersecurity field.

With the number of cyberattacks growing with each passing day, the need for increasingly sophisticated security systems has never been higher. Just when these ceaseless attacks had you at your wit’s end, machine learning may just restore some sanity to the cybersecurity scene.

We can all agree that it’s almost impossible for a human being to forecast what means or measure the next attacker will adopt to breach your prized security protocols. This is where machines come into play! A subset of artificial intelligence, machine learning can be used to train machines to analyze, detect, and even terminate any sort of suspicious activity that might pose a threat to a business. With the right kind of training, machines have the capability to detect new, previously unheard of threats; put a stop to anomalous activities; recognize malicious behaviors; and much more.

With machine learning, your security team won’t have to spend hours poring over unbelievably huge amounts of data generated by your environment. (Go ahead, team, break into your happy dance.) Tasks traditionally performed by security analysts can be automated and executed in time to catch suspicious activities, before they can cause any real damage. This is a great way to avoid errors and eliminate human bias for consistent and positive results.  

The cybersecurity stage seems to be beckoning for machine learning to join the picture and save us all from the endless list of cyberattacks. However, there seems to be different opinions on machine learning’s ability to fight cybercrime. Let’s take a look at five interesting reads from around the web that represent those positions.

  1. AI’s Biggest Impact in the Data Center is Cybersecurity: It is impossible for human beings to analyze huge amounts of data fast enough to detect malicious entities. Machine learning can do this on our behalf and has the ability to address the gaps that may exist in your current security posture.
  2. 6 Ways Hackers Will Use Machine Learning to Launch Attacks: Despite all the hype, machine learning can be a double-edged sword. If it can help the good guys deflect attack, it can also help criminals launch sophisticated attacks. Stay one step ahead of them always by learning some of the common ways machine learning can help malicious agents.
  3. Applying Machine Learning to Advance Cyber Security Analytics: Detecting zero-day vulnerabilities like ransomware can be tackled effectively with a combination of machine learning and your company’s usual security measures.
  4. The Truth about Machine Learning in Cybersecurity: Defense: Train your machines well enough and they can accurately predict, classify, and cluster threats as well as recommend the appropriate actions to be taken for these threats.
  5. Does Cyber Security Really Need Machine Learning Technology? Machine learning might not be the magic formula to solve all of your security challenges, but it’s definitely a necessary addition for your security arsenal.

Machines may not be the comprehensive solution you need to combat the rising number of security threats, but, adopting an intelligent systemic approach that can detect and counter threats in a timely fashion is where machine learning steps in. Not only can it increase your chances of evading attacks, but it can also help boost your organization’s overall security measures.

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Priyanka Roy
Marketing Analyst