When it comes to the technology backing an enterprise, ensuring the security of networks and data has to be a high priority. This may sound glaringly obvious but oftentimes companies lack direction when it comes to building this kind of software. This is where cybersecurity comes in.

In today’s world, cyber security is non-negotiable for anyone with sensitive data stored online. Take for instance the fact that there are an estimated 2,200 cyber attacks per day which equates to over 800,000 per year and 1 every 39 seconds. 

This raises a ton of red flags for many businesses that are now forced to evaluate their options for protection consistently. It's also important to remember that technology is built to adapt and needs to be in order to tend to the needs of its surroundings. 

When it comes to the case of a company protecting its assets, there are many factors to consider both within and outside the organization. One way that companies are addressing the growing threat of cyber attacks is through the use of machine learning.

Machine learning is a technology that can perform without being directly ordered to carry out specific functions. As you may have guessed, this means its capabilities are incredibly versatile and you’d be right. When it comes to cybersecurity, here is how machine learning is used to enhance its performance:

3 Ways Machine Learning Is Used For Cybersecurity

1. Pattern Recognition: Machine learning uses algorithms that can realize patterns in data and identify any irregularities that might indicate a breach. Machine learning is especially effective at detecting malware, a type of hacker software designed to cause disruption. This is something that traditional methods may struggle to identify.

2. Attack Prediction & Prevention: Machine learning is used to predict and prevent cyber attacks before they ever happen. For example, an algorithm could be used to help a company that’s already experienced cyberattacks by analyzing the company's past attacks and identifying the common patterns or indicators that suggest a future attack. Companies can then take this information and develop contingency plans as well as take preventative measures.

3. Improved Security: Aside from simply detecting and preventing attacks, machine learning can improve the overall security of a company's networks and systems. For example, machine learning can be used to monitor network activity and identify potential vulnerabilities. This information can then be used to patch those vulnerabilities and strengthen the company's overall security posture. Features of this include: 

Fraud detection: Machine learning can analyze data transactions and identify patterns that may suggest fraudulent activity.

Malware detection: As mentioned earlier, machine learning algorithms can also be trained to recognize patterns in code that might indicate the use of malware; this allows them to identify and block malicious software before it can cause any harm.

Phishing recognition: Machine learning can even be used to analyze the contents of an email and identify patterns of a phishing attack.

For Small Businesses:

Small businesses often have limited resources and may not have the same level of security as larger enterprises. However, this does not mean that they are immune to cyber-attacks. In fact, well over 40% of online attacks are targeted at small businesses due to their perceived lack of security measures. This makes it even more important for small businesses to have strong cybersecurity systems in place.

Machine learning can be a valuable tool for small businesses looking to improve their cybersecurity posture. By automating the detection and prevention of cyber attacks, small businesses can protect their sensitive data and ensure the long-term sustainability of their platforms.

The Takeaway

Machine learning can enhance cyber security by equipping companies with the most advanced tools and tactics to detect and prevent attacks, in addition to improving the overall security of the companies' networks and systems. As the threat of cyber attacks continues to grow, the use of machine learning in cyber security is inevitably going to continue expanding through innovation. If we were to get into specifics, experts are predicting a Compound Annual Growth Rate (CAGR) of nearly 9% over the next 5 years in the industry. 

As we’ve seen here, machine learning is already a highly valued tool when it comes to security and preventative measures for cyber attacks or any other variant of digital fraud for that matter. Companies who are serious about the long-term sustainability of their platforms' secure information storage are making the necessary moves using the right software. But as always, it starts with reviewing the needs of your business to find what is right.

Written By Ben Brown

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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.