Support Intelligence –

Artificial Intelligence

like a Rock

Icewater is a clustering technology leveraged to organize data objects based on how they look. Icewater converts any document, binary, or program from any architecture into a representation and then using the same algorithms found in nature compares the objects. Turns out this is a really fast way to identify malware and malicious documents. Who would have thought that nature would have invited these algorthims.

Leveraging parallel compute, Icewater is able to calculate Object Cluster Identifiers at an average of 0.5 milliseconds per compute core providing for a scalable way to test everything. Icewater can leverage GPUs and FPGAs for blinding speed in a index everything attitude

One million samples a day
Clustering as Life and Art

Icewater is fast, energy efficient and scaleable. Our base system handles more objects on server class CPU than most of our competitions clustered solutions. COTS Hardware or VM or Cloud the architecture doesn’t matter to Icewater. Clustering provides a data triage capability so your sandboxes or analysts can focus on the unique targeted attacks.

 

Never before have we had the amount of data to sift sort and analyze than we have today in cyber security. Early security researchers noted the similarity to biological metaphors of viruses and those labels were adopted by the computer/tech world. Icewater actually uses algorithms derived from nature.

 

Every one of your cells, your dog or cat’s cells, the cells in the hamburger you ate or the sausage biscuit you had used the same algorithm to organize its cells DNA. Trillions (you have about 3 trillion cells in your body) use this same algorithm to keep your DNA organized.

 

When you sit and discuss leveraging Icewater to solve your cyber security issues, ask each and everyone of your cells if they should pick a different algorithm. The only organisms on the planet that don’t use this to organize their DNA are Bacteria and Archaea.

Details

Unique hardware allows us to process orders of magnitude more samples. Leveraging NVidia GPUs that are both energy effici  ur network and when it detects a matching malware sample.

 

Sandboxing takes time and ICEwater dialiates time by using nature’s mathematics against malicious actors.

 

Don’t sandbox malware that has been detected, leverage your sandbox for the unknown unknowns.

 

Scalability

The Parallel Compute architecture of Icewater provides benefits to organizations in three different ways.


Flexible

Icewater can be deployed on general purpose servers,virtual machines, or on AWS, or in any architectural combination preferred by your organization. This also means that Icewater can be deployed quickly and be operational the same day.

 

Cost-Effective

Icewater employs a subscription-based pricing model based on the compute capability required to support the deployment. This makes it simple and cost-effective to adjust deployment based on the needs of the organization.


Scaleable
Icewater scales linearly in order of Millions of samples per day in one unit of rack space.

 

Hardware Exceleration

 

Compute Model:

CPU 16-core 
Objects per Day: 250,000

GPU NVidia GForce 1080, Object per Day 1,200,000

FPGA Altera Stratix IV : (call) Govt Only [no export]*

Xenon Phi / Knights Landing (Beta)* exportable

Amazon AWS G2 and P2 instances

2 Million Objects / day depending on network and disk provisioning, may be clustered to provide unlimited objects per day


Minimum interface speed: 10Gb

 

* Can be clustered to provide over 10M objects/day

About Icewater 
and Support Intelligence

Icewater is developed by Rick Wesson at Support Intelligence, a Internet Security Startup based in the Bay Area. The patented technology incorporated in Icewater leverages the same algorithm your DNA uses to keep from becoming tangled in knots.

 

We are looking for investors that want to drive security up the assholes of the badguys by making it exponentially harder for them to operate on gobal networks. When you are ready to start winning, let us know.

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