How Machine Learning Can Combat Cybersecurity Threats : Future of Cybersecurity

Nowadays businesses store large amount of data, which is really important for them. But, integration with software and hardware has now increased very much so, keeping data safe and secure has become very difficult. The software used by the cybercriminals nowadays give rise to many concerns in security organization. Due to this the criminals has now become a threat player who can easily disseminate and penetrate their target organization with the help of some never seen or customize malware. As a large amount of data is parsed and analyzed always so, it becomes impossible for the users to filter, analyze, and make operational decisions depending upon the information gathered by the infrastructure system. Thus, cybersecurity has found out a new way of dealing with these type of cyber criminals by using the powerful abilities of machine learning algorithms. These algorithms make it easy for the computers to analyze a large amount of data and make decisions. Hence, this blog will let users know how machine learning can advance cybersecurity in detail.

The Need of Machine Learning in Cybersecurity

Technology nowadays moves really fast and manual cybersecurity practices are no longer sufficient to keep businesses, government and other companies safe and secure. Some of the main reasons are discussed below:

• There is a large amount of security-related data approaching on the network from the array of connected devices
• A number of qualified personnel are very less that can guarantee proper integration between the multiple systems. They provide security-related data to the Security and Event Management systems whose aim is to detect the intruder cases.
• It might also be possible that a risk is identified and prioritized by the security analysts. But, there may be a delay in communicating that threat to the system administrators and network engineers that charged to tackle the issue.
• All such conditions have a very bad impact on the cybersecurity as there are too many false positives and fake alarms that detract the security analyst in finding and combating real threats.

Considering all above-stated points, it is clear that role of Machine Learning in Cybersecurity is really important for cyber threat intelligence .

Use Machine Learning to Advance Cybersecurity

As there is a large amount of data is in use and coming from multiple sources so, detecting cybersecurity events by a human is becoming difficult. Therefore, for a cybersecurity to be relevant and effective, it must make a use of Machine Learning in Cybersecurityto cope up with the today’s hybrid environment. Predictive analytics of machine learning renders a powerful use case that is helpful for cybersecurity. It is an area of network and cybersecurity, which perform some amazing things i.e., identify and pick up anomalies in traffic connections, patterns, user activities, etc., in the aspects of the network. Apart from all this, cybersecurity uses machine learning to detect following events:

 

• High Risk Third-party Apps Control: To detect malicious or harmful third-party application that is installed in the environment and can compromise data.
• Protection from Ransomware: Strong detection and rectification of infection that can affect the environment.
• Detection of Data Leakage: It will look for an unusual data patterns, which might correspond to leakage of unauthorized data.
• Control Sensitive Data: Look for the sensitive data, which is stored in the emails or documents and perform the appropriate action on them accordingly.

In addition to this, Machine Learning in Cybersecurity can also be used to detect many more cybersecurity events based on the requirements. All of these are powerful tool to secure the environment of an organization.

Automating Tasks of Cybersecurity Via Machine Learning

The Machine Learning in Cybersecurity approach helps in automating the several cybersecurity tasks, which can easily deploy in real time. It can detect any malicious activity before it leads to damage.

It is because a properly trained machine learning model has the ability to determine the out-of-the-way traffic on the network and can shut down these connections immediately. It can also identify the all new samples of malware, which are aimed at fudging human generated signatures and try to isolate these samples before they are executed.

Concluding Thoughts

Machine learning is exciting technology that is used for data analysis and intelligent computing. With the help of or power of Machine Learning in Cybersecurity, it becomes easy for the businesses today to make proper use of the large amounts of data. Moreover, it would be very difficult for humans to combat sophisticated cybersecurity threats. Therefore, organizations make use of machine learning to advance cybersecurity.