The Importance Of On-Premise Computer Vision For Phishing Detection

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Given the major challenge posed by phishing today, which continues to grow at exponential rates, this article discusses why phishing detection platforms should be looking at on-premise computer vision as an essential additional layer in their tech stack.

Phishing Attacks – A Major Challenge

The challenge facing cybersecurity professionals is immense and growing larger by the day. The already steep upward trend in phishing attacks worsened when COVID struck, culminating in a monthly record of 260,642 attacks in July 2021, according to figures released by the Anti-Phishing Working Group (APWG).

These are bleak figures, which look even more concerning when considered from a financial viewpoint, given that according to Cybercrime Magazine, the predicted costs to businesses in 2021 is $6 trillion, with the costs expected to increase by 15% annually.

Cybersecurity professionals and IT departments are under intense pressure to tighten security and to take the fight to the bad actors behind the phishing attacks. Further, depending on what data is reviewed, it is reported that upwards of 90% of compromises begin as a phishing attack. Reducing the number of phishing attacks by even a few percentage points can therefore reduce the risk of compromises significantly. One method that is increasingly being implemented is using Computer Vision to visually identify threats.

This relatively new methodology takes a unique approach to identify phishing attacks And is covered in detail in this anti-phishing white paper, available for download.

Human “eyes” at Computer Speed – Visual-AI Leads the Fightback

Escalating arms races of any type will always push the boundaries of technology. Unfortunately, in this case, the nature of the playing field means that bad actors have the upper hand, with security centering on reactive strategies and reliance on blacklists and signatures.

For the security industry, this reliance is a definite Achilles heel. Unavoidable delays in updating blacklists/signatures open windows of opportunity for bad actors.

And this is where computer vision for cybersecurity can level the playing field.

Adding Computer Vision to a tech stack brings Visual-AI to the fight. This method doesn’t rely on blacklists or identifying programmable threats to stop phishing attacks. 

Until recently, this technology was available almost exclusively in a Software-as-a-Service (SaaS) cloud-based format, which had specific limitations when used in phishing detection. But that has changed with the introduction of on-premise computer vision.

The Benefits of On-Premise Computer Vision for Cybersecurity

This new method of implementing computer vision technology bypasses many of the inherent problems of cloud-based SaaS solutions. These include slower processing times and privacy concerns. 

Among the benefits of on-premise computer vision technology are:

1. Processing Time

One major factor affecting the performance of Visual-AI is the requirement to transfer potentially millions of images per day. This necessity can put a massive strain on networks and regardless of the speed and efficiency of the local network, capacity is always limited by the external network infrastructure.

For many organizations, this has meant the major challenge in implementing Visual-AI has been avoiding the latency caused by slower connections. Moving to an on-premise Computer Vision solution is an obvious way of addressing latency caused by network bottlenecks.

2. Privacy and Data Protection

Another issue that faces companies using a SaaS computer vision system, is the need to protect sensitive data. By necessity, using a cloud-based system means that data has to leave a company’s network to be processed.

Naturally, there is a reluctance by many companies in sensitive sectors (finance, medical, law enforcement) to allow highly sensitive data to be exposed to any extra risk (perceived or real), and a cloud-based system represents just that, regardless of the security measures implemented by the cloud provider. 

On-premise computer vision negates the need for data to leave a network and adds an extra layer of security.

3. Cost-effectiveness

SaaS solutions work best when consistent volumes of data are delivered for processing. But in many cases, cyber security companies will have fluctuating requirements; sometimes very high and at other times lower. In these cases, switching to an on-premise computer vision solution would be more cost-effective, as resources can be scaled up and down to meet demand without the worries of contract and pricing changes.

In these instances, on-premise computer vision that deploys a company’s own hardware can be a far more cost-effective solution.

4. It’s a Flexible Solution

The SaaS version of the Visual-AI platform is a flexible option that serves many companies perfectly adequately. However, companies that employ on-premise Visual-AI have found that this solution takes flexibility to a new level.

IT departments run a constant juggling act of allocating finite resources against surges in both user and system demands. On-premise computer vision allows complete flexibility for organizations to react to periods of high and low demand and to allocate the necessary processing power as required.

This is particularly true in phishing detection, where data needs to be processed in real-time and the results returned instantly. This is extremely resource-hungry, so being able to match the resources to precise volume demands is very cost-effective.

5. Can be deployed anywhere

Systems, such as VISUA’s on-premise Visual-AI, have been developed to allow for easy implementation regardless of the existing infrastructure. This “Deploy-Anywhere” compliance adds another level to the cost-effectiveness and flexibility of the platform.

Systems that require specific combinations of hardware can be a major factor in companies implementing these vital technologies while they organize the purchasing and support contracts for the equipment and learning around OS/Software implementation. By simplifying the process and making the system hardware and server agnostic, VISUA has removed one of the major sticking points when it comes to enhancing defenses against phishing attacks.

In Conclusion

The rapidly evolving cybersecurity threats that we all face need a solution that can stand apart from traditional methodologies and stare the threat right in the face. Visual-AI does just this – because it perceives threats from a visual aspect and is largely immune to the ongoing evolution of cybersecurity threats. But truly successful implementation of Visual-AI/Computer Vision in phishing detection needs an On-Premise implementation that is simple to deploy and is designed for the specific needs of its intended use.

This is where VISUA’s on-premise solution stands apart. Book a demo now and organize a proof of concept test within your own environment to discover how Visual-AI can help increase detection rates in your phishing detection platform.

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