Moving Detection Back to the Edge
BluVector delivers intrusion detection for advanced threats, powered by a self-adapting form of machine-learning. Unlike other network security tools which find bad actors once they have infected a host, BluVector delivers high fidelity threat detection pre-install.
BluVector and Machine Learning
Signature / Rules / Pattern Engine
GOAL: Match an explicit string within a given data set.
Unsupervised Machine Learning
GOAL: Find unusual patterns/behaviors within unlabeled data sets by clustering like data and identifying outliers.
Supervised Machine Learning
GOAL: Predict the right answer based on exposure to training data.
|without BluVector||with BluVector|
20 Hours per incident
4 Hours per incident
|~$1740 per incident||~$348 per incident|
|Detection of 1 new targeted/variant threat every 2 days (est. 620 advanced threats evade current tools annually)|
BluVector Awarded SAFETY Act Designation
After a rigorous application and due diligence process the U.S. Department of Homeland Security granted BluVector a DHS SAFETY Act Designation in May 2016. Deploying BluVector as part of an enterprise security ecosystem now includes a level of decreased risk due to this Designation, providing peace of mind relatively few security technologies can provide.
See it in action. Schedule a demo.
Want to learn more? Check these out:
Security vendors are inundating CISOs with products purporting to use artificial intelligence to dramatically improve the accuracy and speed of both threat detection and response. However, much of this messaging is confusing, even misleading. How do you know fact from fiction from enthusiastic marketing? S&R pros should read this Forrester report to understand what is really possible with AI today to take cybersecurity efforts to the next level.
The healthcare industry, like many others, needs to re-examine its threat awareness, network vulnerabilities and malware preparedness. To help, we’re giving you free access to a piece by Gartner called “Simple Lessons You Must Learn From WannaCry.”
WannaCry is just one example in the continuing evolution of malware threats that recently devastated healthcare organizations, causing many IT teams to make a difficult choice, “Do we pay the ransom?
In July 2017, advanced threat detection startup BluVector augmented its machine learning-based analytics engine to detect memory-based attacks in real time. This means the BluVector Network Security Monitoring and Analytics platform leverages a new network emulation technique to identify a broader spectrum of attacks coming from both malicious files and embedded file attacks executed in memory.