Netskope named a Leader in the 2022 Gartner® Magic Quadrant™ for Security Service Edge. Get the Report.

  • Products

    Netskope products are built on the Netskope Security Cloud.

  • Platform

    Unrivaled visibility and real-time data and threat protection on the world's largest security private cloud.

Netskope Named a Leader in the 2022 Gartner Magic Quadrant™ for SSE Report

Get the report Go to Products Overview
Netskope gartner mq 2022 sse leader

Netskope delivers a modern cloud security stack, with unified capabilities for data and threat protection, plus secure private access.

Explore our platform
Birds eye view metropolitan city

Make the move to market-leading cloud security services with minimal latency and high reliability.

Learn more
Lighted highway through mountainside switchbacks

Prevent threats that often evade other security solutions using a single-pass SSE framework.

Learn more
Lighting storm over metropolitan area

Zero trust solutions for SSE and SASE deployments

Learn more
Boat driving through open sea

Netskope enables a safe, cloud-smart, and fast journey to adopt cloud services, apps, and public cloud infrastructure.

Learn more
Wind turbines along cliffside
  • Our Customers

    Netskope serves more than 2,000 customers worldwide including more than 25 of the Fortune 100

  • Customer Solutions

    We are here for you and with you every step of the way, ensuring your success with Netskope.

  • Training and Certification

    Netskope training will help you become a cloud security expert.

We help our customers to be Ready for Anything

See our Customers
Woman smiling with glasses looking out window

Netskope’s talented and experienced Professional Services team provides a prescriptive approach to your successful implementation.

Learn more
Netskope Professional Services

Secure your digital transformation journey and make the most of your cloud, web, and private applications with Netskope training.

Learn more
Group of young professionals working
  • Resources

    Learn more about how Netskope can help you secure your journey to the cloud.

  • Blog

    Learn how Netskope enables security and networking transformation through security service edge (SSE).

  • Events & Workshops

    Stay ahead of the latest security trends and connect with your peers.

  • Security Defined

    Everything you need to know in our cybersecurity encyclopedia.

Security Visionaries Podcast

Episode 14: Enabling Security from the Top-Down

Play the podcast
Black man sitting in conference meeting

Read the latest on how Netskope can enable the Zero Trust and SASE journey through security service edge (SSE) capabilities.

Read the blog
Sunrise and cloudy sky

SASE Week

Netskope is positioned to help you begin your journey and discover where Security, Networking, and Zero Trust fit in the SASE world.

Learn more
SASE Week

What is Security Service Edge?

Explore the security side of SASE, the future of network and protection in the cloud.

Learn more
Four-way roundabout
  • Company

    We help you stay ahead of cloud, data, and network security challenges.

  • Why Netskope

    Cloud transformation and work from anywhere have changed how security needs to work.

  • Leadership

    Our leadership team is fiercely committed to doing everything it takes to make our customers successful.

  • Partners

    We partner with security leaders to help you secure your journey to the cloud.

Netskope enables the future of work.

Find out more
Curvy road through wooded area

Netskope is redefining cloud, data, and network security to help organizations apply Zero Trust principles to protect data.

Learn more
Switchback road atop a cliffside

Thinkers, builders, dreamers, innovators. Together, we deliver cutting-edge cloud security solutions to help our customers protect their data and people.

Meet our team
Group of hikers scaling a snowy mountain

Netskope’s partner-centric go-to-market strategy enables our partners to maximize their growth and profitability while transforming enterprise security.

Learn more
Group of diverse young professionals smiling

Say What? Natural Language Processing Improves Cloud Security

Nov 03 2020

Coauthored by Ben Xue and Yi Zhang

This is the third entry in a series of articles focused on AI/ML.

Natural language processing (NLP) is a form of artificial intelligence (AI) that gives machines the ability to read, understand, and derive meaning from human languages. NLP powers many applications that we use every day, such as virtual assistants, machine translation, chatbots, and email auto-complete. The technology is still evolving very quickly. Just over the last few years, we have seen incredible breakthroughs in NLP research, including transformers and powerful pre-trained language models such as GPT-3, which have significantly accelerated the development of NLP applications in various domains. 

At Netskope, we are integrating the latest NLP technology into our secure access service edge (SASE) solution, as well as business operations. NLP is behind the scenes for a wide variety of tasks, including:

  • Detecting sensitive information in documents to help our customers comply with privacy regulations and protect their digital assets. 
  • Categorizing and detecting malicious web domains, URLs, and web content to enable web filtering.
  • Detecting malware and protecting enterprise assets from being compromised and used as a launchpad for malicious activities.
  • Classifying SaaS and web apps and evaluating the enterprise readiness of a cloud app as part of the Cloud Confidence Index (CCI). 

In this blog post, we will highlight three ways Netskope uses NLP to secure data and protect against threats: DLP document classification, URL categorization, and DGA domain detection.

DLP Document Classification

Various documents from our customers are stored in their cloud storage or transferred through cloud applications. Many of these documents contain sensitive information, including confidential legal and financial documents, intellectual property, and employee or user personally identifiable information (PII). At Netskope, we have developed machine learning-based document classifiers, as part of our inline Data Loss Prevention (DLP) service. The ML classifiers automatically classify documents into different categories, including tax forms, patents, source code, etc. Security administrators can then create DLP policies based on these categories. The ML classifiers work as a complementary approach to traditional regular expression-based DLP rules and enable granular policy controls in real-time. In many cases, manually configured regex rules can generate excessive false positives or false negatives when looking for specific patterns in documents. In comparison, the ML classifiers automatically learn the patterns and identify sensitive data in real-time, without the need for traditional DLP rules.

Flowchart showing document classification process
FlowFigure 1. DLP document classification flowchart

Text classification is one of the standard NLP tasks. As illustrated in Figure 1, we extract the text content from documents and use a pre-trained language model as an encoder to convert documents into numeric values. Based on the document encodings, we then train document classifiers in the form of fully connected neural network layers. Currently, the classifiers are able to accurately identify more than 10 types of documents with sensitive information, including:

  • Source code
  • IRS tax forms
  • M&A forms
  • Resumes
  • US patent files
  • Offer letters
  • Bank statements
  • Non-disclosure agreements
  • Consulting agreements
  • Partner agreements
  • Stock agreements
  • Medical power of attorney forms
Image showing types of sensitive documents

The light-weighted document classifiers are able to run inline to provide real-time data protection for our customers.

URL Categorization

Web content filtering helps organizations to regulate access to websites that may have offensive, inappropriate, or even dangerous content. NLP-based URL categorization is responsible for grouping websites into different categories based on their text content, which enables web content filtering.

Imaged showing approved and blocked URL categories

Traditionally, a text classification machine learning model is trained for a specific language. With the latest development in NLP, it is possible to train a multilingual classifier that supports multiple languages. The training data can be a mixture of text in different languages, and the trained model can predict the category of the new text, regardless of which language it is expressed in. We have developed multilingual URL classifiers with the state-of-the-art transformer language model BERT that supports over 100 languages. Based on the content that is crawled dynamically, the classifiers accurately identify websites in many undesirable categories, including weapons, drugs, adult content, criminal activities, etc. 

DGA Domain Detection

Modern malware, such as botnets, ransomware, and advanced persistent threats, typically makes use of a domain generation algorithm (DGA) to avoid command and control domains or IPs being seized or sinkholed. It is important to detect DGA domains automatically in order to block malicious domains and identify compromised hosts. Traditional DGA detection techniques rely on collecting the contextual information (e.g., IP, NXDomains, HTTP headers) of the domains and blacklisting. In comparison, machine learning-based DGA domain detection has the potential to identify unknown DGA domains. 

Flowchart showing DLP Domain Detection

On the surface, determining whether a domain such as intgmxdeadnxuyla.com is DGA or not has nothing to do with natural language processing. Actually, it is very similar to an NLP task if we treat each character in the domain name as a word and the full domain as a sentence. We can then use NLP techniques to learn the semantic relationship between the characters and the overall meaningfulness of the domain. We have developed a DGA domain classifier based on Long Short-Term Memory Networks (LSTM), a Recurrent Neural Networks architecture commonly used in NLP. Based on millions of training samples, the LSTM classifier captures the context information in each domain by treating it as a sequence of characters and classifies it as DGA or non-DGA with high accuracy.

Future of NLP

This is a golden era for natural language processing. NLP models are getting faster and more powerful by the day. At Netskope, we will provide better data and threat protection to our customers with the latest NLP technology. What problem are you trying to solve? Contact us at [email protected] to share it with us.

author image
Ben Xue
Hongfa "Ben" Xue joined Netskope in January 2020 as a Data Scientist. Specifically, developing several NLP applications using deep learning. Ben received a BS in Computer Science from Beijing University of Posts & Telecommunications in 2015 and then joined George Washington University to pursue a PhD in ECE, with a research interest in machine learning and system security.