Artificial Intelligence

The escalating influence of generative AI on business and cybersecurity in 2024: its growing adoption, potential challenges, and the critical need for regulatory oversight.

Some cybersecurity vendors say they provide AI but only deliver basic rule-based systems. Ask 4 questions to see if an AI in cybersecurity claim is real.

The Cambrian Explosion in large language model (LLM) AI SaaS services has opened a huge number of exciting opportunities for everyone, however there are some giant risks associated with these services. As people continue to leverage them regardless of risk — Vectra helps you track exactly who.

What do you need to know following the announcement of the integration of Vectra's Attack Signal Intelligence into Amazon Security Lake?

As threats become more prominent, it’s important to pose the question: what actually brings clarity? It’s a question that we can struggle with, but we may simply not be approaching it in the right way.

Looking for an alternative to Darktrace? See why 9 in 10 customers choose Vectra AI, the top Darktrace alternative powered by Attack Signal Intelligence.

Discover how Vectra AI, through user feedback, has improved its scoring model and user interface to provide more effective threat prioritization and an efficient workflow.

Vectra CRO Willem Hendrickx why he's excited about the opportunity ahead for AI in cybersecurity.

Last week SentinelOne announced integrations with key industry players inclulding an enhanced collaboration with Vectra AI to expand the company’s XDR offering.

72% of security practitioners "think they may have been breached, but don't knowit." Said differently, nearly three-quarters of security teams don't know wherethey are compromised right now.

When an analyst detects an intrusion, the most critical factor is analyzing the context of the intrusion. We do this by identifying the attacker’s tactics, techniques, and procedures (TTPs).

With KPMG's guidance and Vectra's technology, organizations can achieve greater visibility into their security posture, reduce risk and reassure the protection of their critical data.

Through harnessing Vectra's Security AI-driven Attack Signal Intelligence (ASI) for cloud, SecOps teams can continuously monitor and uncover sophisticated threats across their SaaS and cloud environments in real-time.

2022 brought a surplus of geopolitical drama and the world's first full-on cyberwar. What comes next? Here's an educated estimate.

Modern cyber threats are increasingly evasive and difficult to detect. Vectra offers a new AI-driven solution: Attack Signal Intelligence.

In August 2022, the Vectra Protect team identified an attack path that enables malicious actors with file system access to steal credentials for any Microsoft Teams user who is signed in. Attackers do not require elevated permissions to read these files, which exposes this concern to any attack that provides malicious actors with local or remote system access.

If you ask security analysts to describe the biggest pain points in their role, you will no doubt get a diverse set of answers. One thing that they will almost certainly have in common is the challenge of dealing with alert fatigue.

"Artificial intelligence is no match for human stupidity," observed a wry Albert Einstein. Today, we have evolved to where AI can deliver critical and indispensable advantages in the race toward cybersecurity. Nevertheless, even brilliant security managers do not always see how or why this is the case.

Dive into the intricacies of AI in cybersecurity with Vectra AI's 'Not All AI is Created Equal'. Learn about the distinction between security-led and math-led AI approaches, and discover how Vectra's unique, data-driven strategy offers superior threat detection and response capabilities, setting a new standard in AI-driven cybersecurity solutions.

Explore the real impact of AI and ML in cybersecurity with Vectra AI's blog 'The Great AI/ML Debate'. Uncover the truth behind the buzzwords and learn how AI-driven solutions can effectively counter modern security threats, including ransomware attacks.

Every year the world of cybersecurity encounters new challenges and obstacles for organisations to overcome, but 2021 managed to be an exceptionally dangerous year. So how will the lessons learnt from 2021 shape the cybersecurity landscape? Here are four areas of cybersecurity that will evolve in 2022.

Asking the right questions to your vendor is critical to dissociate the trendy marketing wording from reality. Asking questions such as "What type of machine learning algorithms does your product use?" will help. Discover the top nine questions we think you should ask.

Exclusive cybersecurity research presented in a new report, details how hundreds of security leaders are addressing today's complex cyberthreats in their organisations.

CISOs Must be Brave Enough to Throw Away Their Security Playbook or Suffer the Consequences!

Vectra has been recognized as a DeloitteTechnology Fast 500™ award winner - a ranking of the fastest-growing technology, media, telecommunications, life sciences, fintech, and energy tech companies in North America.

"Do your part" is the theme of this year's Cybersecurity Awareness Month. See what you can do right now so cyberattacks don't become a problem in your Microsoft cloud environment.

Many organizations these days face incident response challenges. Get insight about the common challenges in this area, and what your organization can do to resolve them.

AI can save your SOC valuable time by automating workloads, while accurately tracking down cyberattacker activities found in ransomware and supply chain attacks.

Ransomware. It is the new digital bogeyman. In the UAE, an industry survey from June 2021showed the extent to which the country (and by implication, the wider region)has been subjected to ransomware. Some 37% of respondents said they had beenvictims in the previous two years. A staggering 84% elected to pay the ransom, only for most of them - 90% of those who paid - to suffer from second attacksthat often came from the same bad actors.

Vectra Detect cybersecurity solution is purpose-built to detect and stop ransomware attacks. The agentless and AI-driven Cognito Platform sees and stops ransomware before it can encrypt files and exfiltrate data by automatically detecting attacker behavior.

After obsessing for years over pushing the limits with AI to detect cyberattacker behavior, Vectra is proud to hold the most patents referenced in MITRE D3FEND.

Vectra is key contributor to new CEPS Report on the Technology, Governance and Policy Challenges of AI and Cybersecurity and supports Vectra's mission to make the world a safer and fairer place.

Announcing extended coverage of Vectra in your entire AWS cloud footprint using the new AWS traffic mirroring capabilities on EC2 instances based on the popular Xen platform.

In 2020 we got a glimpse of just how much AI is beginning to penetrate everyday life. However, practical applications raise important questions about the ethical use of AI. In this blog, we reflect on the biggest stories in AI from last year.

Vectra CTO Oliver Tavakoli looks back on a disruptive 2020 and shares his view of what 2021 holds for security practices.

With the advent of AI, managed security service providers (MSSPs) have a huge opportunity to improve 24x7 network threat detection, response and visibility while augmenting their understanding of security events.

AI-based detections are great at identifying attacker behaviors while threat intelligence provides fast, labeled coverage of known threats. Adding threat intelligence extends the coverage of AI-based detections to give you the most durable coverage and early understanding of threats.

Learn why using AI models to look for the communication pattern of a RAT in network data, can help detect them in real-time with high-fidelity based on the behavior observed.

Imagine having a security tool that thinks the way you teach it to think, that takes action when and how you have trained it to act. No more adapting your work habits to generic rules written by a third party and wondering how to fill in security gaps that the rules did not tell you about.

In just the last few years, numerous studies have been published and institutes inaugurated that are dedicated to studying which jobs of the future will remain in the hands of humans, and which will be doled out to the machines.

The use of AI in cybersecurity not only expands the scope of what a single security expert is able to monitor, but importantly, it also enables the discovery of attacks that would have otherwise been undetectable by a human. Just as it was nearly inevitable that AI would be used for defensive purposes, it is undeniable that AI systems will soon be put to use for attack purposes.

In the last blog post, we alluded to the No-Free-Lunch (NFL) theorems for search and optimization. While NFL theorems are criminally misunderstood and misrepresented in the service of crude generalizations intended to make a point, I intend to deploy a crude NFL generalization to make just such a point.

Despite the recent explosion in machine learning and artificial intelligence (AI) research, there is no singular method or algorithm that works best in all cases. In fact, this notion has been formalized and shown mathematically in a result known as the No Free Lunch theorem (Wolpert and Macready 1997).

Deep learning refers to a family of machine learning algorithms that can be used for supervised, unsupervised and reinforcement learning. These algorithms are becoming popular after many years in the wilderness. The name comes from the realization that the addition of increasing numbers of layers typically in a neural network enables a model to learn increasingly complex representations of the data.

There are numerous techniques for creating algorithms that are capable of learning and adapting over time. Broadly speaking, we can organize these algorithms into one of three categories-supervised, unsupervised, and reinforcement learning.

"The original question "Can machines think?' I believe to be too meaningless to deserve discussion. Nevertheless, I believe that at the end of the century, the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted." - Alan Turing

Can machines think? The question itself is deceptively simple in so far as the human ability to introspect has made each of us intimately aware of what it means to think.

It is difficult to tell the history of AI without first describing the formalization of computation and what it means for something to compute. The primary impetus towards formalization came down to a question posed by the mathematician David Hilbert in 1928.

The random forest (RF) model, first proposed by Tin Kam Ho in 1995, is a subclass of ensemble learning methods that is applied to classification and regression. An ensemble method constructs a set of classifiers-a group of decision trees, in the case of RF-and determines the label for each data instance by taking the weighted average of each classifier's output.

Cisco recently <a href="https://newsroom.cisco.com/press-release-content?type=webcontent&articleId=1854555" target="_blank">announced</a> the term "intent-based networking" in a press release that pushes the idea that networks need to be more intuitive. One element of that intuition is for networks to be more secure without requiring a lot of heavy lifting by local network security professionals.

Time is a big expense when it comes to detecting cyber threats and malware. The proliferation of new malware variants makes it impossible to detect and prevent zero-day threats inreal-time. Sandboxing takes at least 30 minutes to analyze a file and deliver a signature-and by then, threats will have spread to many more endpoints.

Security breaches did not stop making headlines in recent months, and while hackers still go after credit card data, the trends goes towards richer data records and exploiting various key assets inside an organization. As a consequence, organizations need to develop new schemes to identify and track key information assets.The biggest recent breach in the financial industry occurred at JP Morgan Chase, with an estimated 76 million customer records and another 8 million records belonging to businesses stolen from several internal servers. At Morgan Stanley, an employee of the company's wealth management group was fired after information from up to 10% of Morgan Stanley's wealthiest clientele was leaked. Even more sensitive was the largest health-care breach thus far: at Anthem, over 80 million records containing personally identifiable information (PII) including social security numbers were exposed. Less well-known, but potentially more costly in terms of damage and litigation is the alleged theft of trade secrets by the former CEO of Chesapeake's Energy (NYSE: CHK).

Keeping data from getting out into the wild or being damaged by cyber attackers is what keeps CISOs, the executive team and boards of directors up at night. To protect organizations, cybersecurity needs to be automated and real-time, it needs to learn contextually like we do and it needs to monitor for threats at every corner of the network in a way that organizations can afford without sacrificing coverage.

Not all breaches come from external malicious actors. Learn all about insider threats, the common indicators and useful prevention strategies in our blog post.