MIxmode Blog
MixMode Product Updates, Stories on Cybersecurity, AI, and Everything in Between.
Featured Content
How MixMode’s AI Builds Your Network’s Baseline
Here we describe the type of information that Mixmode’s AI system “looks” at for decision-making, and emphasize how it is human-like in behavior but with a substantially enhanced computational capacity.
Leveraging MixMode to Monitor AWS Cloudtrail
Learn how MixMode ingests your CloudTrail logs into our platform and apply a layer of our Proprietary AI to give you advanced anomaly detection and alerting.
Anomaly Detection with Unsupervised AI in MixMode
Here we will discuss some of the opportunities and challenges that can arise with anomaly detection as well as MixMode’s unique approach to the solution using Unsupervised AI.
ALL BLOGS
Consider investing in emerging tech tools that can add a deeper layer of data privacy protection. Artificial intelligence technology, in particular, holds a great deal of promise when it comes to complying with the CCPA and improving the way companies handle data in general.
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The cybersecurity provider landscape is cluttered with impossible claims, misrepresentations, and a confusing mix of inconsistent terminology. Worse, every minute you delay making a decision is another minute hackers have to gain access and knowledge about your network.
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Knowing the difference between Discriminative and Generative Unsupervised Learning can tell you a lot about the effectiveness of a cybersecurity solution’s artificial intelligence, for example, whether or not that security solution can perform actions like identifying and stopping a zero-day attack.
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This is the final article in a three-part series on Network Baselining. Read the first two articles in the series here:
1) An Introduction to Baselining Technology
2) How to Create a Baseline for Your Network
We separate the parts that are wavelike and we separate the parts that are stochastic. Then, five minutes later we look again and compare what we’ve seen historically and what the AI has predicted to happen to the current state of the network. If they are different, that’s an anomaly detected.
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In October, 2019 a MixMode customer experienced an incident where an external entity attacked a web server located in their DMZ, compromised it, and then pivoted internally through the DMZ to attempt access of a customer database. While the attacker was successful in penetrating the customer’s network, MixMode was able to detect the event before they were successful in penetrating the customer database.
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This is the first installment of the three part blog series on creating baselines of network behavior to improve your security stance. Here we will walk you through the basics of baselining technology.
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Today we announced a small but exciting update to MixMode’s Network Traffic Analysis platform! We have made performance and usability updates to the indicators page below: The Indicators page has been completely re-architected for a tremendous improvement in speed and performance. I urge you to go and try it for yourself right now – you …
What’s New in MixMode: November 2019 Read More →
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The best way to detect threats across an entire network in the quickest manner is to have complete visibility over every part of that network with a multi-stream platform which can incorporate not only network data, but Cloud Data and SIEM logs as well.
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Alert fatigue is a top pain point in cybersecurity right now. Security operations center (SOC) analysts are chasing an overwhelming amount of false positive alerts taking time away from analyzing and remediating actual security threats. According to a recent study…
Read MoreAbout MixMode
MixMode is the first to bring a third-wave, context-aware AI approach that automatically learns and adapts to dynamically changing environments. MixMode’s monitoring platform, PacketSled, better understands network behavior as it adapts to baseline changes and enables both misuse detection and anomaly detection, as well as predictive maintenance. Used by enterprises and MSSPs for real-time network analysis, threat hunting and incident response, the platform leverages continuous stream monitoring and retrospection to provide network forensics and security analytics. Security teams can integrate PacketSled into their orchestration engine, SIEM, or use PacketSled independently to dramatically reduce false positive alerts and the resources required to respond to persistent threats, malware, insider attacks and nation state espionage efforts.
The company has been named an innovator in leading publications and by security analysts, including SC Magazine, earning a finalist award in 2018 and 2019 for "Best Computer Forensic Solution.” Based in Santa Barbara, with offices in San Diego, the company is backed by Keshif Ventures and Blu Venture Investors. For case studies, continuous product updates and industry news, please visit us at www.mixmode.ai.