Zero-day threats

3 Reasons Why a Rule-Based Cybersecurity Platform Will Always Fail

| | Blog, False Positive Alerts, false positives, labeling, NDR, Network Baselines, Network Security, network traffic analysis, Predictive AI, Self-Supervised AI, SIEM, Zero Day Attacks, Zero-day threats
When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats ...
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The Many Ways Your Employees Can Get Hacked While Working From Home and How to Respond

| | Blog, coronavirus, COVID-19, Cyber Threats, cyberthreats, Malware, Network Security, network traffic analysis, Phishing, threat actors, threat detection, Uncategorized, Unsupervised AI, Zero Day Attacks, zero-day attack, Zero-day threats
Although it is not surprising at all that hackers are taking advantage of the global pandemic —phishing threat reports are always highest when there is some natural disaster happening— we have never ...
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Yesterday’s SIEM Solutions Can’t Combat Today’s Cyberthreats

| | AI network monitoring tools, Blog, Context Aware AI, Network Detection and Response, SIEM, threat detection, Threat Hunting, Unsupervised AI, Zero Day Attacks, zero-day attack, Zero-day threats
While it’s true that having a SIEM is better than forgoing network monitoring all together, a standalone SIEM solution is simply insufficient in today’s cybersecurity landscape. Hackers and other bad actors have ...
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Hacking the Hackers: Adversarial AI and How to Fight It

| | AI, AI Cybersecurity, Blog, Ransomware, threat detection, Unsupervised AI, Zero Day Attacks, zero-day attack, Zero-day threats
Advances in Artificial Intelligence (AI) have led to smarter, more robust network security platforms that are quickly replacing legacy security solutions ...
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Generative Unsupervised Learning vs. Discriminative Clustering Technology: Which Prevents Zero-Day Attacks?

| | AI, Artificial Intelligence, Blog, machine learning, Network Detection and Response, threat detection, Unsupervised AI, Zero Day Attacks, Zero-day threats
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 ...
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Case Study: MixMode AI Detects Attack not Found on Threat Intel

Case Study: MixMode AI Detects Attack not Found on Threat Intel

| | AI Cybersecurity, AI network monitoring tools, Blog, case-study, Cyber Threats, Cybersecurity using AI, Network Detection and Response, network traffic, threat detection, Unsupervised AI, zero-day attack, Zero-day threats
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 ...
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4 Ways to Protect Your Business from Zero-Day Attacks

4 Ways to Protect Your Business from Zero-Day Attacks

| | Blog, Third Wave AI, Unsupervised AI, Zero Day Attacks, zero-day, zero-day attack, Zero-day threats
Zero-day attacks cost businesses millions of dollars in lost revenue and recovery costs and can cripple a company that is not prepared to respond decisively and effectively ...
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How MixMode’s AI Builds Your Network’s Baseline

How MixMode’s AI Builds Your Network’s Baseline

| | AI, AI Cybersecurity, AI Network monitoring, AI network monitoring tools, Context Aware AI, Cybersecurity using AI, False Positive Alerts, False Positives in Network Security, Network Detection and Response, Reduce False Positives, Third Wave AI, Uncategorized, Unsupervised AI, zero-day attack, Zero-day threats
Mixmode’s platform utilizes third-wave, context-aware AI to inform the user of threats (including Zero-Day, and encrypted traffic) on their network, and reduces the rate of false positives in intel and alerts consistently ...
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