Deep learning and cybersecurity
It’s time to fix your perimeter security
Deep learning is a powerful new technique to detect threats in fast-moving businesses. In fact, by applying deep learning to the complete network flow, you can detect threats in real-time, and stop patient zero or further lateral movement in your environment. There are a variety of different benefits for different personas and industries deploying our Blue Hexagon Real-Time Deep Learning Platform.
A recent survey carried out by ESET found that Americans are most worried about a cyberattack disrupting the financial/banking system, more than attacks against hospital/emergency services, voting systems, or power grid/energy supply companies.
In fact, financial services firms fall victim to cybersecurity attacks 300 times more frequently than businesses in other industries. While the typical American business is attacked 4 million times per year, the typical American financial services firm is attacked a staggering 1 billion times per year. Among financial services firms, banks lost $16.8 billion to cybercriminals in 2017.
The good news is unique security technologies such as our real-time deep learning platform can help you keep pace with attackers. Before you invest in other parts of your network, fix your perimeter security. Signature and sandbox-based detection are simply not effective for today’s threat landscape.
Using a deep learning based platform enables your security teams to stop Patient Zero and further propagation in the network. More importantly, our platform works with your existing security products today to ensure you can optimize the products that you’ve already invested in.
Our platform delivers:
- Threat detection and prevention in less than one second which translates to tremendous cost savings from a potential breach as well as operational efficiencies getting ahead of remediation and response.
- One high-value platform for detection of known and unknown network threats. This means not only cost savings with product consolidation but less complexity with debugging.
- High efficacy verdicts and low false positives ensure that precious cybersecurity resources will not need to be dedicated towards debugging, tuning or triage.
- Orchestrated prevention with existing endpoint, firewall and network security devices ensure investment in existing security products are preserved.
In the past 5 years, cyber attacks against healthcare organizations have increased. The reason for this trend is that attackers have figured out that healthcare data is extremely valuable, increasing in value, and very difficult for victims to generate new ones.
In fact, Ponemon Institute calculated the average healthcare data breach costs to be $380 per record. In contrast, the average global cost per record for all industries is $141. This means that data breach costs are more than 2.5 times the global average. Additionally, it took more than six months on average to detect an incident, with an average of 55 days or almost two months to contain it.
Our deep learning platform can help. Extremely easy to deploy and requiring no local tuning or baselining, our platforms works out-of-the-box on day one for security teams.
Our platform delivers:
- Easy deployment via network TAP or SPAN. Our platform works out of the box on day one, without incurring learning delays or requiring any human triage
- Real-time threat detection against known and unknown threats including top attacks such as ransomware. According to the 2018 Verizon Data Breach Investigations Report, ransomware makes up 85% of malware discovered in healthcare organizations. Our deep learning platform has been proven very effective in detecting polymorphic malware and zero day malware variants that target healthcare organizations.
- Complete threat visibility–threat families, top threat trends, indicators of compromise, complete kill chain context–are provided to ensure that healthcare security teams have key threat insights available to them for threat intelligence and proactive operations.
Massive retail data breaches in recent years such as Target and Home Depot have helped your industry develop learnings for stronger, more comprehensive cybersecurity strategies.
Yet, retailers continue to top the list for cyberattacks. This is no surprise — retailers store and have access to critical customer and credit card information that are extremely attractive to attackers. Retailers also work on multi-channel partner and customer acquisition strategies to enhance the customer experience, and this approach opens up many opportunities for attacks.
In fact, today’s attackers are innovating using AI and automation, and launching cyber threats at a volume and velocity that evades existing security solutions.
Our deep learning platform gives you an advantage. By identifying threats in less than a second, you can keep up against the fastest attack, stop them and prevent data exfiltration of critical customer data and credit card information.
Our platform delivers:
- The highest efficacy with threat verdicts compared to traditional machine learning or legacy security solutions such as signature and sandboxes threat detection solutions. Our deep learning model optimization can support retail multi-gigabit traffic requirements
- Proven results with the speed of threat detection in real-world environments. In fact, threat inference in less than a second sets a new standard for threat detection today.
- Unique pricing strategy for retailers with hundreds and thousands of locations. Annual threat subscription is based on bandwidth of traffic inspected.
- The backing of Blue Hexagon Labs on strategic initiatives such as staying ahead of threats via our daily Global Threat Cloud