We are living in a world that is full of technologies; the most advanced is artificial technology. Artificial technology has further sub-techs like machine learning and deep learning. AI and all the tech-based advanced systems of artificial intelligence are improving human life by making it easy to elaborate. In this article, we will discuss some advantages of machine learning. Tech use is necessary for every business and “where is good there is a bad too”. Cyber attacks are very common these days and are an increasing threat to every business day by day. The importance of artificial intelligence and machine learning increasing in this regard as they can analyze millions and billions of data sets in a short time and ascertain and hunt down cyber threats.
What are the benefits of machine learning in cyber security?
Before going on the advantages of machine learning in cyber security we should know what is cyber security. Here it is…
What is cyber security?
Protecting computer systems, networks, devices and sensitive data from theft, damage, and illegal access is known as cybersecurity. To protect networks, devices, and confidential material from cyberattacks; including the use of technologies, processes, and practices.
Some advantages of machine learning in cyber security.
A boon to cyber security is machine learning, multiple prons of machine learning in boosting cyber security are below…
Capable of handling huge data analysis.
Every business has a huge number of data sets of their customers, products, employers, vendors and businesses. Machine learning allows investigating this large set automatically with an automation system of machine learning algorithms which is quite impossible to do manually in a short time; when machine learning algorithms detect threats then they are automatically dealt with.
Enhanced accuracy and early threat detection.
Algorithms and models of machine learning continually learn, study, gain experience and improve themselves by learning from previous data and previous threats. ML models detect cyber attacks with more accuracy and earlier and allow operators to stop them some actions before significant damage to data.
Improved incident response and reduced duplicative Processes.
Machine learning algorithms and models regularly and frequently serve in the investigation and prevention of basic, common and complex security risks. It also runs a full examination of the network to determine the threats; if there are any security problems that can be dangerous to your network ultimately allows the managers to take action against threats. Machine learning algorithms and models automate the incident response procedure and assist security teams in quickly remediating security incidents.
Predictive analysis and authentication safety.
Models of ML are capable to predict cyber attacks in the future through an analysis of previous data of threats and through these predictions; researchers can build new and advanced systems to secure their data. Machine learning algorithms also secure the account of users while logging in; secure their account through CAPTCHA, face and fingerprint recognition also include passwords and pin numbers to avoid any unauthorized identity to use other’s account.
User behavior modeling and analysis.
ML algorithms are pre-trained to take a look at the behavior of users like their normal logging time, and daily routine activity; when the algorithm of machine learning found an irregular activity or irregular timing of logging it takes it as an alert and notifies the original user.
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