• Meghan Taylor, freelance at N/A


• 23.08.2021 02:45 pm
#cybersecurity #cybercrime

Cybercrime is one of the biggest threats to a business’s security in 2021. Businesses must be continually aware of the cyber threats that are out there, that are evolving continuously and be able to mitigate against these in the best way that they can. Cyber security has always been difficult to handle for all types of businesses, but especially the FinTech industry. Fortunately, machine learning is helping to change this situation.

Machine learning is a branch of artificial intelligence (AI) that involves the computer using data analysis and algorithms to analyse and develop, ‘learning’ without the need for human input.

With this in mind, here are five ways that machine learning can help to improve cyber security:

1. Machine Learning can incorporate Human Input

Machine learning is not only about letting the computer do all of the work. Humans can also be involved. Some jobs still need to be done by people. For example, the computer can look quickly at large amounts of data and pick out potential security threats or unusual patterns, which can then be thoroughly investigated by a human – work that cannot be done by a computer.

The computer can provide statistics and reports as well as classifying threats in terms of potential danger.

2. Machine Learning can detect Present and Evolving Threats

Cybercrime by its very nature is changing all of the time. And at a pace that is far too quick for humans to keep up with. For example, where ransomware was once the biggest threat to a business’s security, the main problem at the moment is coin-mining, attacking systems that use cryptocurrencies such as Bitcoin. 

Machine learning can help to detect these existing and evolving threats as well as help to see when they are developing, helping businesses to stay completely up-to-date and protect themselves, their data, and assets from threats.

3. Machine Learning can shorten Response Time

When it comes to security of any nature, time is of the essence. The sooner a security breach is recognised and dealt with, generally speaking, the more effective the response. And this is also true of cybercrime. Catching a breach of security early will normally mean less initial damage and more effective response from the business.

Machine learning can be employed to look for anomalies or patterns that can suggest a security breach in real-time, immediately drawing attention to potential risks, and, therefore, allowing for a quick response – much quicker than humans could analyse the data and deal with the response. It can also respond to certain threats, by shutting down certain parts of a system, for example, as soon as it detects an irregularity, automatically protecting the system.

4. Machine Learning can deal with Exponential Data Systems’ Growth

The world of data systems is no longer confined to a single building, system, or even format. Businesses have increasing numbers of people working remotely, across a number of different systems, and even using different formats – no longer is it just text-based emails that are used to communicate within businesses.

There are no longer boundaries for security systems to work within, and this exponential growth of data systems can be impossible for traditional security systems to cope with adequately, which is why many SaaS data integration tools “allow endpoint protection, encryptions, and anomalous behaviour detection” say experts at Gravity Data. 

Machine learning can effectively deal with these developments to an infinite degree.

5. Machine Learning can Predict Future Threats

In the fast-paced world of cybercrime, it is not always enough to be up-to-date. Businesses need to be ahead of the game. Using a system that is only reactionary can put a businesses’ cyber security in danger of new risks.

Machine learning can not only look for developments of current threats, but it can also help to predict future threats, helping businesses to stay as fully protected as they possibly can.

For most businesses, cyber security should be one of their highest priorities and something that is taken very seriously. Ensuring that their data and other assets are protected is essential, and when it comes to implementing machine learning to help with cyber security, it is something that businesses cannot afford not to do.