The Leading AI Cyber Security Firms (Part 2)
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In a new era of digital business, companies are being driven to rethink their approach to technology. And there is now more focus on using technology strategically, which forces more collaboration between IT and commercial business units.
And as more organisations prepare to buy AI-enabled security tools, potential customers have a lot of concerns about the best ways to install and use these products, as well as the technology behind them. This Report will help you choose the right organisation for your protection.
Being closer to the cutting edge means that businesses need to have a better understanding of which technologies can directly be adopted and which ones are security safe to engage with enabling more comprehensive solutions.
Among the many emerging technologies that companies are exploring to gain a competitive edge is Artificial Intelligence (AI).
But it’s security is often misunderstood.
This research report provides context for the state of AI adoption, describing general perceptions around the concept, current implementation status, and hurdles in the way of future success.
Artificial intelligence may be closer than ever, but there are still security steps to take before it is fully integrated into everyday business.
Using a broad definition for AI, many existing IT activities could be placed on an AI spectrum, and building on these activities could lead to better automation or stronger data analysis.
However, most companies take a modern view of AI, imagining use cases such as personalised customer experience or security incident detection.
Along with the introduction of new AI components, companies must also consider the infrastructure needed, the data that will drive the work, and the processes for integrating AI into workflow.
Furthermore, the skill set required to develop modern AI is not a simple extension of existing software skills. There are certainly new algorithms to learn, but there are also new concepts around training these algorithms and reverse engineering unexpected results.
As much as companies may be adding experience in software development, true AI development requires a new way of thinking.
Of course, most companies will not perform their own AI development. Their adoption of AI will come in the form of products that incorporate these new software methods.
The Business Case for AI
The question of how AI is being used in the enterprise is closely related to the question of what AI is in the first place. Given a fluid definition over the years, many existing IT components could once have been classified as mimicking human intelligence.
The development of Artificial Intelligence (AI) has begun to appear in a lot of different IT products, including in the field of cyber security and corporate analysis.
Improvements in technology is being driven by competition and developments that includes new innovations by a number of firms and organisations.
And as more organisations buy AI-security tools, there has been a number of concerns raised about the technology and the best ways to implement and use these products.
Specifically, vendors need to understand how a customer will ensure the data used to train and run an AI-enabled security product is high in fidelity and free from bias.
The field of cyber security is very active at the moment, with new techniques and attack prevention methods appearing almost every day and we would like to highlight the leading AI cyber security organisations that are really effective and currently operating.
But first we will succinctly discuss the concept of AI.
Artificial Intelligence
AI is a blanket term that shifts over time as computing becomes more powerful, then this most recent incarnation has specific characteristics that are worth understanding.
As the name implies, AI or Artificial Intelligence is not natural, and it is a simulation of how the human mind works. Much like a machine, the human brain controls all function of an organism.
For example, how the mind managed active functions and another is autonomous responses that are basically knee-jerk responses. More technical know-how is available to give machines an iota of sentience, like self-driving cars and interactive robots that can manage without human assistance.
Look at the brain, once scientists could only dream of making something as good as the human brain. Now we have computers that are made up of electronic components, to make computer approximate what is human thinking.
For example, every biological component has an electronic part that approximates how machine work in the real world. AI constructs have sensors that are similar to sight, hearing, touch, and feeling that is almost similar. Human operate on the same idea, but are biological machines based on carbon, and AI is steel and electronics.
One requirement to make AI this responsive and smart is using lots of data, the human mind has the most data in nature. Teaching machines with AI, allow them to do tasks smartly, and better than humans.
Three concepts in particular play a large role in defining the unique properties of modern AI.
Machine Learning. To a large extent, machine learning is actually the end goal for most of the cutting-edge work in AI.
Machine learning generally refers to techniques that allow computers to gather data and build their own pathways for analysing that data. There is no single approach or algorithm that defines machine learning; instead, there are many different methods being used to produce machine learning capability.
This means that an end user needs to know the details behind the specific machine learning process they are implementing.
Deep Learning. Deep learning is one of the most common approaches for machine learning. With deep learning, computers analyse problems at multiple layers in an attempt to simulate how the human brain analyses problems.
Visual images, natural language, or other inputs can be parsed into various components in order to extract meaning and build context, improving the probability of the computer arriving at the correct conclusion.
Neural Networks. These software models consist of five parts, a decision-making unit called a neuron, inputs, weights that can be assigned to the inputs, biases that shape the analysis, and a single output (also called an activation function). Multiple stages of neurons can be stacked together to result in the multi-layered analysis found in deep learning.
AI Concept
AI is not so much a new tool or product as it is a new concept. Fully understanding this concept and putting it to use requires an appreciation for how AI fits into the overall IT plan.
It starts with data, consolidating all corporate information together in order to properly train an AI system and then feed in the appropriate inputs. It extends to the other technology initiatives in a company, so that AI is integrated with existing systems and innovative solutions.
The final step is applying AI results to business processes, recognising that when AI comes close to human intelligence, it is making an educated guess that can still be balanced by workforce expertise.
With that in mind, organisational data capabilities should be a prime consideration for AI readiness. Very few companies feel that they are exactly where they want to be in terms of how they manage their data.
This could mean some degree of dissatisfaction at any stage of the data process, from capturing new data streams to data storage and manipulation to data- driven decision making.
The same deficiencies that would have kept companies from fully embracing big data models will be an impediment to AI adoption.
AI is the application of heuristics, or a shortcut, that allows problems to be solved and judgements can be made quickly to distinctly improve programming.
Rather than running through a list of instructions like a procedural programming language, AI methods maintain a database of instructions and act on data as variable. The selection of the next action to take relies on the application of probabilities.
This methodology enables the programs to write their own rule bases by tracking activities on a network. The longer a program is resident, the less likely it is that your business’s activities will be crippled by “false positives” that cause the security software to shut down internet access and close down programs.
Machine learning and variable workflows have transformed the cyber security industry but current analysis suggests that come next year 2021, cyber-crime losses will cost upwards of $6 trillion.
Because effective information security requires smarter detection, many cyber security companies are upping their game by using Artificial Intelligence to achieve that goal.
Now AI is being used as a cyber security tool to find and mend system vulnerabilities continuously and as cyber criminals develop new ways of penetrating IT systems and so organisations must try to stay on watch and AI will help the process.
From a benefit perspective, companies are still focused on a traditional IT viewpoint around cutting costs. AI can help with cost savings, but the greater potential lies in opening new doors. Nearly half of all companies are hoping to discover new insights, but these must be factored into a new decision-making process rather than taken as gospel.
Most AI activity today is happening within companies with the resources to perform their own AI development, but over time AI will become more and more productised.
For businesses to truly reap the benefits of AI beyond moderate improvements to existing processes, they will have to embrace the changes necessary for handling probabilistic results and build the capabilities needed for managing massive quantities of data.
In Alphabetical order here are some of the top cyber security companies for AI implementation you should review and consider using:
Click Here To Go To Part 1 Of This Report:
In 2019, Trend Micro’s Zero Day Initiative (ZDI) disclosed 171% more high severity vulnerabilities than in 2018. The criticality score reflects the likelihood of these flaws being leveraged by attackers, so high severity bugs are more likely to be weaponised and the patches should be prioritised.
Japanese cybersecurity company Trend Micro recently signed an agreement on scientific and technical cooperation with Kazakh security firm T&T Security, to support a government initiative known as the “Concept of Cyber Security” or “Kazakhstan Cyber Shield.”
The new partnership is intended to develop and implement local projects in the field of information security in Kazakhstan.
As per the alliance, T&T Security integrates Trend Micro’s existing security solutions to monitor suspicious network activity, malware threats, prevent intrusions, and protect servers and workstations from potential cyber risks.
Trend Micro incorporated, a global leader in cybersecurity, helps to make the world safe for exchanging digital information. In an increasingly connected world, our innovative solutions for businesses, governments, and consumers provide layered security for data centers, cloud environments, networks, and endpoints.
With 30 years of security expertise, Trend Micro has significant accolades: The market leader in server security since 2009, according to IDC, the most effective recommended Breach Detection solution five years running, according to NSS Labs, and a Leader in both the Gartner Magi
Quadrant for Endpoint Protection Platforms and the Forrester WaveTM for Endpoint Security Suites. These solutions are powered by XGenTM security, a cross- generational blend of threat defense techniques.
Our products work together to seamlessly share threat intelligence and provide a connected threat defense with centralized visibility, enabling better, faster protection and time to response. No matter what the security need, or how it may evolve over time, Trend Micro is the smart security choice.
Trend, which has offices all over the world, was very fast to has directly informed all of the customers when some of its information was stolen by the rogue insider, and the security specialist warned its consumer customers to be wary of any unsolicited calls claiming to be from Trend support staff.
This situation of course reflects the problem all security and commercial operations have with problem employees.
But Trend dealt with the situation very well and quickly.
"We immediately started investigating the situation and found that this was the result of a malicious insider threat," Team Trend said in announcing the leak. "The suspect was a Trend Micro employee who improperly accessed the data with a clear criminal intent.
Trend has also found and fixed several critical vulnerabilities in its products, two of which it warned are being exploited in the wild.
The security giant released patches for Apex One and OfficeScan XG on Windows, urging customers to upgrade to the latest versions “as soon as possible."
CVE-2020-8467 is a critical zero-day a vulnerability in the migration tool component of Trend Micro Apex One and OfficeScan. It could allow remote attackers to execute arbitrary code on affected machines.
Such discoveries are not uncommon in an industry more focused than most on ensuring products are bug-free.
With phishing being the single most effective way for an adversary to target an organisation, Trend Micro has integrated detection and response across endpoints and email to produce more insightful investigations.
With the leading attack source covered, analysts can trace a root cause analysis back to email to identify all impacted parties, contain the threat, and stop the spread.
Trend Micro goes beyond endpoint by implementing cross-layer detection and response (XDR) across endpoint, email, cloud workloads and network to remove constraints on enterprise security teams and offer a consolidated view of attack paths across security layers. As a result, Trend Micro’s EDR capabilities are part of a more robust Trend Micro XDR platform offering.
Trend Micro Incorporated, is a global leader in cyber security solutions, and it helps to make the world safe for exchanging digital information. It has innovative solutions for consumers, businesses, and governments provide layered security for data centers, cloud environments, networks, and endpoints.
All their products work together to seamlessly share threat intelligence and provide a connected threat defense with centralised visibility and control, enabling better, faster protection.
With more than 6,000 employees in over 50 countries and the world’s most advanced global threat intelligence, Trend Micro enables organisations to secure their journey to the cloud.
Vade Secure is one of the world's leading email defense companies, deploying artificial intelligence and machine learning to protect more than 600 million mailboxes in 76 countries from a variety of threats including spear phishing, ransomware, and malware.
One of Vade Secure aims is to help SM protect their users from advanced cyber threats, such as phishing, spear phishing, malware, and ransomware. The company's predictive email defense solutions leverage artificial intelligence, to block targeted threats and new attacks from the first wave.
Vade Secure has recently release of its own research on the most common mechanism through which cyber attackers commit their ransomware scams via phishing attacks.
According to Vade Secure’s Phishers’ Favorites Q4 2019 report, attackers continue to impersonate some of the world’s largest brands to trick email recipients into believing their scams, and for corporates, the most common brand used is Microsoft.
In addition, real-time threat detection capabilities enable SOCs to instantly identify new threats and orchestrate coordinated responses. Vade Secure's technology is available as a native, API-based offering for Office 365; as cloud-based solutions; or as lightweight, extensible APIs for enterprise SOCs.
Vade Secure for Office 365 is an award-winning email security solution that provides comprehensive, automated protection before, during, and after attacks.
Fed by threat intelligence and user feedback from 600 million protected mailboxes worldwide, Vade's patented AI-based technologies, including machine learning, computer vision, and natural language processing, detect highly targeted phishing, spear phishing/business email compromise, and ransomware attacks.
The solution goes beyond threat detection with AI-based auto-remediation to automatically remove any threats that reach users' inboxes.
Vectra has a cloud-native Cognito platform that automates security operations that are usually carried out by in-house security staff. Network metadata is extracted and analysed by sensors in order to operate machine learning and detect threats, before allowing for quick response.
Vectra Networks Inc. is based in San Jose, California.
It was founded in 2010 and exists solely to implement AI in cyber security software. Originally called TraceVector LLC, the business incorporated in 2012 under the name of Vector Networks.
The company focuses its activities on one product, which is called the Cognito platform. This is a threat detection system that deploys AI methodologies to establish a baseline of activity throughout an enterprise and identify anomalies.
The system doesn’t include automated responses to detected threats, so it can’t be classified as a unified threat manager, or an intrusion prevention system.
The analysis engine for the system is accessed online and is called Cognito Recall.
Data gathered by the Cognito platform can be transferred up to this storage and analysis facility, or you can pipe data through to Zeek tools (formerly Bro) and use those to analyse data and set up automated responses.
Data transfers and formatting are carried out by Cognito Stream. One more module, Cognito Detect, allows a threat profile to be created and has some automated preventative measures.
Vectra Networks is still a private company. Its list of investors includes venture capitalists Khosla Ventures, Accel Partners, and IA Ventures.
Webroot harnesses the power of AI to stop zero-day threats in real time, securing businesses across the globe with threat intelligence, and providing protection for endpoints as well as networks.
Webroot's principal software engineer in machine learning, Chahm An, said he's used AI since 2014 for phishing attacks and malware, specifically for JavaScript malware as well as other threats online like botnets.
An, has noted, that traditional anti-virus programs essentially created lists of things it knew to protect against, but as the world changed and attacks evolved, and it has become nearly impossible to categorise the volume of threats online.
While there are other phishing solutions available to detect a phishing site, many are based on the metadata or URL, leveraging the old list-based way of doing things. Other companies look for patterns in the URL to detect a phishing site.
However, Webroot's phishing solution works in real time, allowing it to open up the URL and block it from there.
The company also uses machine learning to gain more insight into specifically why certain attacks are bad, in an effort to expand its understanding of the threat landscape.
With its pioneering Zero Networks Access Orchestrator, the Israel-based Zero Networks created a cloud-based network security service that uses artificial intelligence to underpin a zero-trust network model.
Founded in 2019 by Benny Lakunishok and Jossef Harush, Zero Networks develops a cloud-based network security service called the Zero Networks Access Orchestrator, which automatically defines, enforces, and adapts user-and-machine-level network access policies to create a zero-trust network model.
The platform observes how users and machines normally communicate to automatically define and enforce a zero trust network model throughout an enterprise.
The Zero Networks Access Orchestrator, currently being used by beta customers in the manufacturing, energy, retail, and public sectors to defend their internal networks, will be commercially available at the end of Q1 2020.
With a patent-pending two-factor authentication mechanism, Zero Networks allows its customers to make new or rare connections and automatically updates policies so that they can always access what they need, when they need it.
The company has had a quick rise, starting in 2019, and it is already attracting major investors, securing $4.65 million in seed funding in February 2020.
Conclusion - AI Industry Disruption
Artificial Intelligence can be thought of as a very broad spectrum of capability. If the basic definition is “computing that mimics human intelligence,” then most of computing history is actually about the evolution of artificial intelligence, and many of today’s standard IT practices were yesterday’s cutting-edge AI.
Also there is a large difference between human-like behavior in a specific use case and the ability to have that behavior across a wide variety of situations.
By fundamentally understanding what AI is and how today’s AI is different from previous models, people can be more informed about how this trend will fit into business and society.
For established business and newcomers, a fresh take on technology, such as AI can provide them intelligent cyber security and also a wedge to force open potential in crowded and competitive markets.
AI innovations will continue to emerge and change the way a hitherto stable business operates.
Cyber security, along with all of the technology sector will continue to evolve, and the leaders of different industries will change according to their success or failure in adopting new technology and AI is one and is certainly here to stay.
For more information: please contact Cyber Security Intelligence.
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