The open web is a resource that drives constant innovation and efficiency: it’s also, at times, a menace to security and productivity. Web filtering provides employees with the freedom to browse the web, connect with colleagues, and collate ideas while protecting them from the endless spam, malware, and distractions the web can offer.
At its core, content filtering software identifies and then blocks access to specific websites. Identification can take a number of different approaches:
Some sites are universally incompatible with a productive and appropriate workforce – and DNS filtering allows for complete domain names to be removed from an employee’s roster.
This can block access to:
However, there’s an issue with relying solely on DNS filtering for access management: it’s static, and presents employees with a highly restrictive and sometimes very bypassable wall – an employee just needs to find a more niche site that’s less likely to have been blacklisted.
This places an increased strain on the admins who must then stay on top of this filter bypassing.
Even worse, if a domain is falsely blacklisted, such as a marketing employee being blocked from accessing Facebook ads, legacy content filters can be uniquely frustrating and clunky.
Network-level blocking is essentially a URL classification problem, where you have a list of URLs with some metadata. Deciding whether the specific URL should be blocked or is a simple classification problem is an issue, and it’s tempting to automate with machine learning.
However, Oleksandr Paraska (of the popular Adblock browser extension) conducted a talk on this exact approach being taken within his company: machine-learning network-level blocking is 50 times slower than their manually-created filter lists.
But that’s just for blocking at the DNS level — AI applications do present a better way.
More automated content filtering works by identifying patterns within potentially malicious content – and then using these as signifiers when assessing a user’s site request.
This can be strings of texts, color palettes, or certain objects commonly associated with specific types of content.
For instance, a page with lots of flesh-colored tones sometimes be an indicator of inappropriate content – more precise patterns allow for an employee’s role to be taken into account before allowing or denying content. Good filtering software relies on a backbone of DNS-level blocking, alongside content recognition processes that can identify patterns on web pages and files in near real-time.
Content filtering – when conducted properly – can offer swathes of improvements across employee productivity and security.
Ad filtering software is one of the most commonly-used pieces of content filtering software. It can help retain employee concentration and efficiency – and can also keep them safe from ad-hosted malware.
DNS filtering safeguards organizations from exploit kits, which are often distributed through malicious websites. These exploit kits can compromise browsers or extensions, leading to:
By blocking access to such harmful sites, DNS filtering helps protect sensitive information and maintain network security.
In a more microscopic lens, pattern recognition for malicious content can also be used to identify malware-infected files before they’re downloaded onto an endpoint and executed.
A large number of phishing attacks rely on spoofed pages that mimic their legitimate counterparts – content filtering can identify discrepancies between alleged domain names, and identify suspicious similarities to genuine login or payment pages.
These are generally data points that aren’t immediately visible to an end-user.
For small enterprises, every GB of bandwidth matters: content filtering is an effective method for preventing traffic spikes. Non-essential sites, such as YouTube and Twitch, can significantly increase bandwidth consumption, especially when large groups of users stream content at the same time.
Restricting access to these high-bandwidth sites is a practical way to conserve network resources.
Traditional web filtering systems weathered large amounts of employee dissatisfaction, as they likely wouldn’t know of a webpage’s inaccessibility until after they’re denied access.
This frustration can be avoided by showing the employee what pages can be accessed via their search engine: with a small verification mark, they can quickly understand what pages are safe and which present a risk – before running headfirst into the firewall.
Check Point’s next-generation firewall goes far beyond the simple block-or-deny process that holds legacy content filtering back.
Its base URL filtering process allows for a new degree of granularity, offering the choice to block or allow entire site domains, or specific pages within a website, and the identification of concerning content is powered by market-leading analysis.
Deep packet inspection allows for in-depth traffic analysis even for encrypted traffic, making it applicable even when running on VPNs.
Granular exceptions allow for privacy to be maintained, even while securing employee endpoints.
Get all of this real-time firewall data delivered to the central dashboard, and spot how malicious sites are being levied against your enterprise. Integrate it with Check Point Harmony for ultimate protection scalability and keep all managed and unmanaged devices secure.