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Answering the five most common web filtering questions (Lenovo NetFilter Blog)

Five common web filtering questions answered

With device use in schools becoming more common, the use of web filtering is growing in popularity as a means to keep students safe online. But not all web filters share the same features and functionality — or the same efficacy rates. 

Selecting the best web filter for a school can be a challenge given the number of options available on the market. It is important to understand the differences between web filters and how they operate. Here are the answers to five common web filtering questions schools are asking: 

What is web content filtering? 

Web content filtering is the process of monitoring the web content being accessed through an organization’s network and/or on one of its devices in addition to restricting content that is suspected of being inappropriate or dangerous.  

It is accomplished using web filtering hardware or software, the latter of which may be installed locally or accessed through the cloud, depending on the solution. 

Typically, web content filtering is used by enterprises and organizations like schools, rather than individuals. 

Why is web filtering important? 

Web filtering is an important tool when it comes to protecting students from digital dangers such as explicit content, inappropriate contact and concerning online conduct as well as ecommerce threats.  

For example, a simple cyber threat like malware can be delivered through websites,  when a user clicks an infected download link or loads a page that contains malware embedded in an advertisement (malvertising).  

Web filters often include threat detection capabilities that recognize potentially dangerous content and block it. This includes blocking the download or execution of known or suspected malware. 

Why do schools use content filters? 

Schools use content filters for a several key reasons: 

  1. Security

This may come as a surprise, but schools are by far the most common enterprise-level targets for malware. Student data is a treasure trove for cyber criminals looking to steal or sell identity information on the dark web. Moreover, ransomware attacks on schools are common and can be devastatingly costly. Web filters can be a school’s first line of defense in stopping ransomware and other malware attacks by detecting and blocking suspicious web sites. 

  1. Blocking inappropriate content

Web filters can also be used to block content that is inappropriate for students in a learning environment, including content that is explicit, violent, exploitative, or otherwise objectionable. Many schools also choose to block content that is distracting, such as social media, games, video sites, and online forums.  

  1. Compliance

Another major reason schools use web filters is to stay in compliance with guidelines and regulations, including CIPA, COPPA, the IWF, Friendly Wi-Fi, and others. In fact, schools are required to have a web filter in place in order to receive federal E-rate funding. 

  1. Student Health and Safety

Web filters sometimes include keyword alerts to flag concerning conversations taking place between students on the school’s devices or network. Concerning conversations may include keywords related to self-harm, violence, or cyberbullying. Flagging these conversations for review gives school leadership and parents an opportunity to intervene if appropriate. 

  1. Network bandwidth

Filtering high-bandwidth programs, like online games, YouTube videos, and streaming content can be a smart way to preserve the school network’s bandwidth to ensure better service during peak school hours. Networks can experience significant slowdowns when multiple students access resource-hogging websites at the same time, potentially disrupting learning for other students. 

What are the different types of content filters? 

Typically, content filters will be delivered in one of three ways: 

  • Hardware – Sometimes a web filtering appliance is installed alongside the school’s networking gear. The downside of web filtering appliances is they only work on the school’s network, meaning content is not being filtered when students learn from home.
  • Software – Similarly, certain web filters are delivered as traditional software, which can be installed in the school’s data center. Like hardware appliances, they will not protect school devices when they’re being used on a student’s home network or any other network outside of campus.
  • Cloud-based software – Cloud-based web filters are hosted by the vendor, rather than the school, and are delivered through the Internet. Therefore, they continue to filter content even when a protected device is being used outside of the school’s network.

What makes AI filtering a better choice? 

The cyber threat landscape evolves on a minute-by-minute basis. Web filters can approach threat detection in a couple of ways: 

  1. Importing lists of known threats – Cybersecurity teams around the globe are constantly working to identify new malware and delivery paths for that malware (i.e. compromised websites) in order to share that information broadly with other security teams. Some web filters work by regularly importing the most up-to-date threat lists (e.g. on a daily, weekly, or monthly basis) and automatically blocking any sites or files on that list.
  2. Artificial intelligence – AI-driven filters may import lists of known threats but also include the ability to identify, analyze, categorize, filter, and block suspicious websites and files on their own, keeping everything current. Relying on outdated data, lack of updates or maintenance leads to patching resulting in security breaches. This can also make meeting regulatory compliance more difficult.

This means AI-driven web filters are able to block zero-day threats — threats that have not yet been identified by cybersecurity researchers. This functionality is more critical than ever because cyber criminals are now creating new malware threats faster than in years past. In 2017, zero-day threats represented around 30% of malware, whereas they represented 67% of malware in Q3 of 2021.  


For more web-filtering, check out our very own Lenovo NetFilter page here.