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DEEP LEARNING

Top 10 Applications of Deep Learning.

Deep learning convolutional neural networks and Recurrent Neural Networks RNNs can be applied to create smarter ID/IP systems by analyzing the traffic with better accuracy.

Detecting Trace of Intrusion

Traditional malware solutions such as regular firewalls detect malware by using a signature-based detection system.

Battle against Malware

Natural Language Processing (NLP), a deep learning technique, can help you to easily detect and deal with spam and other forms of social engineering.

Spam and Social Engineering Detection

Deep learning ANNs are showing promising results in analyzing HTTPS network traffic to look for malicious activities.

Network Traffic Analysis

Tracking and analyzing user activities and behaviors is an important deep learning-based security practice for any organization.

User Behavior Analytics

It is vital to keep an eye on the official Email accounts of the employees to prevent any kind of cyberattacks. For instance

Monitoring Emails

Deep learning is already going mainstream on mobile devices and is also driving voice-based experiences through mobile assistants.

Analyzing Mobile Endpoints

The main benefit of deep learning is to automate repetitive tasks that can enable staff to focus on more important work.

Task Automation

WebShell is a piece of code that is maliciously loaded into a website to provide access to make modifications on the Webroot of the server.

WebShell

Deep learning can be used to analyze previous cyber-attack datasets and determine what areas of the network were involved in a particular attack.

Network Risk Scoring

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