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Why Self-Learning Email Security Tools are Important

By Enterprise Security Magazine | Monday, June 15, 2020

Today, phishing has become a huge threat for businesses, so they need to apply proper anti-phishing that can secure their confidential data.

FREMONT, CA: The phishing threats are continuously increasing at a large scale. But most of the business does not have the money, resources, and time required to investigate all the suspicious emails as swiftly as the phishing mitigation demands. In reality, it takes 6-20 minutes for the companies to recognize and remove a phishing email. Therefore, it is surprising that identifying and finding a solution for the phishing is so long that employees can engage with the phishing emails for 82 seconds or less.

Every day almost 350, 00 new types of malware get discovered, and cybercriminals are continuously enhancing their tools and techniques. This is the primary reason for which the traditional methods of response to a phishing incident like secure email gateways (SEGs) have become useless. These conventional methods are mostly dependent on the rules and scripts that cannot match the volume and extent of the new email attacks.

How Self-Learning Email Security Works?

Top 10 Information Security Consulting/Service Companies - 2019However, as self-learning, email security is based on both human and machine actions to get smarter in real-time. By utilizing this method, there will be no gap in the time between learning the latest phishing attacks and the technology’s ability to detect, respond, and prevent. Here are some of the significant methods of knowing about self-learning email security tools.

Big Data

It is necessary to have appropriate and the latest data, but it is not possible to train a machine about corrupt or biased data. To overcome this issue, the company must start its operation at the individual mailbox-level and feed the data into the machine learning model. Therefore, when the data is combined with the meta-data, the machines will know about good and evil.

Machine Learning

It is not easy to draw a line among the good and bad emails, but if the source of data is of good quality, then the starting point can also be useful. Machine learning can help find similarities in the phishing emails and know the attacks at scale. Therefore, it can prevent any extensive attacks from being undetected or wasting time and resources of security analysts.

Reinforced Data

Both humans and technology must help the machines to understand whether they have failed, and it must be done efficiently and quickly. Taking this step will allow the system to get retrained on the errors. This is the primary reason for which the process of real-time has become the core of self-learning solutions.

See also: Top Machine Learning Technology Companies

 

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