How is Logo Detection Used in Anti-Phishing

How is Logo Detection Used in Anti-Phishing

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Logo Detection in Anti-Phishing has become an essential asset 

We have discussed numerous times and at length the challenges faced by cybersecurity companies when it comes to staying in step with cybercriminals. From using the highest-end and newest technology to instigate attacks to the use of clever evasion techniques, bad actors are essentially commanding cybersecurity companies to do better, or else. 

So where does Logo Detection come into this? If bad actors are becoming more visual in their evasion and spoofing techniques then it makes sense to tackle it with a visual arsenal.

Suspected Phishing Page - Bank of America
Be Sure To Also Read ->Logo & Mark Detection Technology Overview

Brand Spoofing 

According to Mimecast, more than half of people have landed on a website purporting to be a brand, whether by email, social media, or search engines. Our trust in certain brands has opened up an attack vector that is more powerful and effective than any before. Bad actors are exploiting the power of trust by using familiar and trusted brands as a way to lure internet users into sharing their private information or login details. 

The growth of brand spoofing in the last number of years has been incredible. A report by APWG reveals that between 2018 and 2021, there was an increase of more than 200% in reported cases of brand spoofing and this trend is expected to continue. 

Brand spoofing entails using every possible avenue  to convince consumers that a communication is legitimate. This not only includes the spoofing of email headers and URLs, but even more importantly, key visual elements, such as logos and other brand markers, like colours, trust logos, and even wording It’s a mostly visual attack vector that requires the use of logo detection and other Visual-AI to address. 

Be Sure To Also Read ->Phishing Detection Use Case Overview

Primed to detect commonly spoofed brands

The addition of logo detection into an anti-phishing product sees that the product is primed to detect commonly spoofed brands. Widely imitated brand logos such as Microsoft, PayPal, Netflix, Citi Bank, and so on, are added to the Visual-AI system’s library. New brands can also be added to the system as a preventative measure, which is especially important when it comes to niche areas and interests. This keeps the system a step ahead, allowing it to quickly detect any usage of logos or parodied logos, and stopping attack attempts in its tracks. 

This is an extremely powerful addition for cybersecurity companies, that, if used proactively, could see successful attack attempts drop dramatically. 

However, it is extremely important to ensure that new logos, variants of logos, product and sub-brand logos, along with other related marks and iconography can be added to the library quickly and efficiently without the need for lengthy training, which can extend the window of opportunity for bad actors to exploit victims undetected.

Example of a logo split into multiple parts to avoid phishing detection

Seeing through evasion techniques

Of course, some bad actors are clever enough to avoid using logos so openly and will use evasion tactics to hide the obvious brand markers. For example, they may turn an entire page or email into an image or scramble logos and reassemble them using Javascript. 

A computer vision engine specifically tuned for this task will not care what programmatic tricks the bad actors employ. The system renders all emails and web pages into flat images anyway, allowing logo detection to work its magic and discover any high-risk logos or icons in an instant.

Staying ahead of attackers

Cybersecurity companies are always looking into new technologies and strategies that keep them ahead of attackers. In an industry where players must move fast in order to avoid their name being involved in a large breach, this drive to stay in touch with new tech is imperative. And with all statistics regarding the success of phishing and smishing attacks on the up in recent years, the demand to stay ahead is higher than ever. 

Logo detection is an excellent example of technology that can keep anti-phishing software in tune with the latest techniques employed by bad actors. Logo detection is exactly the kind of technology that can innovate how anti-phishing software works.

Part of a bigger solution

Although Logo Detection plays an important role in anti-phishing, it’s important to be aware that it is a cog in a machine that encompasses other elements of computer vision. When partnered with an existing AI-powered phishing protection system, user protection is increased significantly when computer vision is added into the mix.  

It’s also essential to ensure that your Computer Vision API Providers are continually improving their offering so that new challenges can be quickly addressed. Yes, it’s a never ending task, keeping cybersecurity software as up-to-date and effective as possible, but it’s something that can make a big difference. 

If you’re interested in discussing logo detection and computer vision as part of your anti-phishing solution, we’d love to chat. Fill in the form below and someone will be in touch as soon as possible.

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