Webinar Recap: The Next-Generation AI Powered SOC Platform
One thing is clear: more spend does not equal more security and the next generation of cybersecurity tools will route out these inefficiencies.
Blog
Deep Dive: How much time do security teams spend labeling with Supervised Learning?
Many CISOs and SecOps teams were faced with a gut-wrenching choice: addressing the operational challenges of keeping workers connected, or shoring up vulnerabilities before hackers exploited them. Both options involved time-consuming, repetitive, manual work.
Why a Platform With a Generative Baseline Matters
MixMode creates a generative baseline. Unlike the historically-based baselines provided by add-on NTA solutions, a generative baseline is predictive, real-time, and accurate. MixMode provides anomaly detection and behavioral analytics and the ability to suppress false positives and surface true positives.
Why The Future of Cybersecurity Needs Both Humans and AI Working Together
A recent WhiteHat Security survey revealed that more than 70 percent of respondents cited AI-based tools as contributing to more efficiency. More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.
Our Q2 Top Cybersecurity Insights
Since we determine everything on data here at MixMode, we went into our website data to see which of our Q2 articles got the most traffic over the past few months. Not surprisingly, the majority of our top articles covered topics on the advancement of AI in cybersecurity and network traffic analysis (NTA).
NTA and NDR: The Missing Piece
Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from SIEM deployments, because the data ingest significantly increases the required data aggregation and storage costs typically 3-5x.
The Problem with Relying on Log Data for Cybersecurity
One of the most prevalent issues impacting the effectiveness of security teams who use SIEM as their primary means of threat detection and remediation is the fact that data logs are an attractive medium for modern hackers to exploit.
The (Recent) History of Self-Supervised Learning
Real unsupervised AI spots security issues sooner and predicts future behavior more accurately than older first- and second-wave solutions. Self-supervised AI technology draws on an understanding of the fundamental nature of the network where it lives, an understanding that isn’t possible with supervised-AI.
Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR and NTA
Traditional security vendors offering solutions like SIEM (Security Information and Event Management) are overpromising on analytics while also requiring massive spend on basic log storage, incremental analytics, maintenance costs, and supporting resources.
Redefining the Definition of “Baseline” in Cybersecurity
While many security solution providers promise to protect your network by establishing a baseline of your network behavior, the definition of “baseline” can vary widely.
MixMode CTO Responds to Self-Supervised AI Hopes
Yann LeCun and Yoshua Bengio were recently interviewed by VentureBeat Magazine on the topics of self-supervised learning and human-level intelligence for AI. Our CTO Dr. Igor Mezic sat down with our team to discuss some of the most interesting pieces of the LeCun article, and offer a potential solution to a search for truly self-supervised …
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Why Training Matters – And How Adversarial AI Takes Advantage of It
The following is an excerpt from our recently published whitepaper, “Self-Supervised Learning – AI for Complex Network Security.” The author, Dr. Peter Stephenson, is a cybersecurity and digital forensics expert having practiced in the security, forensics and digital investigation fields for over 55 years. Section 4 – Why Training Matters – And How The Adversary …
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New Video: How is MixMode Different From Today’s Network Security Tools?
With MixMode in the center of a program, we will make all the other security investments that you’ve made, better. So when you send data to your SIEM, when you send data to your SOAR, you don’t want those products to be overwhelmed with false positive alerts, with data you don’t need.
Machine Learning, Deep Learning and Neural Networks, Oh My!
Deep learning makes decisions based upon the data it sees and the data that it doesn’t see but infers from what it does see. This became useful in the AV industry when the adversary introduced polymorphic viruses. These are viruses that change their appearance on the fly and not always in the same way.
4 Challenges of Stand-Alone SIEM Platforms
While SIEM is undoubtedly a step up from unmonitored network environments, the inherent nature of today’s SIEM software often falls short in several important ways. SIEM is an outdated solution for adequately protecting networks within the modern threatscape.
Whitepaper: Self-Supervised Learning – AI For Complex Network Security
Artificial Intelligence – or AI – has become a buzzword since it emerged in the 1950s. However, all AI systems are not created equal. In our white paper, “Self-Supervised Learning – AI For Complex Network Security,” Dr. Peter Stephenson explains the different “waves” of artificial intelligence. He uses the DARPA definitions for each of these …
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Encryption = Privacy ≠ Security
For the past few years, many have been talking about the changing “threat landscape” as it pertains to the increase in zero day, insider and phishing threats. While all of these threats are on the rise, and constitute a concern, there is, perhaps, an even larger shift presenting a threat to enterprises – the shift …
Self-Supervised Learning – The Third-Wave in Cybersecurity AI
The relationship between modern cybersecurity solutions and AI has become inextricable. The unfortunate reality is that even the most talented and responsive SecOps teams are unable to manually catch every threat posed to the sprawling, hybrid networks on which today’s organizations rely. Forward-looking organizations know they need to bring AI and machine learning based security …
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How the Role of the Modern Security Analyst is Changing
As organizations began to rely more heavily on networking to carry out their operations over the past decade, IT teams added security analyst positions. These professionals focused on network security and providing regulatory compliance oversight. Over time, the role of the security analyst has expanded to include threat hunting tasks. That is, evaluating security platform …
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One Thing All Cybersecurity teams Should Have During COVID-19
COVID-19 has caused most corporate businesses that remain open to shift to a work from home, remote workplace. Because of this, the cybersecurity industry has been turned on its head. Security teams went from monitoring and protecting established network environments to quickly pivoting their tools, resources, and oversight to manage a distributed workforce. This has …
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