100% Cloud-Based Advanced Threat Detection

State Of The Art, Next Generation
DeepSentry is state of the art, next generation Advanced Threat Detection that's 100% cloud-based security. DeepSentry combines deep machine learning and predictive security analytics to transform machine data of your endpoint into actionable intelligence in the form of JSON reports.
So you can restrict the functionality of your software to how you intended to use it whenever a piece of software on your endpoint experiences an unexpected change in its typical behaviors. You can stop hackers, exploits and malware from reaching fruition within seconds after your software deviates from its normal behaviors.
DeepSentry uses deep machine learning to automatically learn the full scope of your software functionality from your sources of machine data. When you're satisfied DeepSentry has received enough training about your endpoint, you can upload new sources of machine data for DeepSentry to analyze. DeepSentry analyzes the new source of machine data by comparing the training report of your endpoint to predictive security analytics based on indicators of attack from emerging threats on your endpoint (seen in your new source of machine data) which could compromise the integrity of your endpoint or the security of your network.
100% In The Cloud
DeepSentry is 100% in the cloud so there's nothing to install on your endpoint or add to your network. DeepSentry works in existing networks, with existing layers of security, without any modifications to your networked infrastructure. DeepSentry doesn't have system requirements. No agent software. No manager hardware.

No Intimate Access To Sensitive Data On Your Endpoint

Secure & Confidential
DeepSentry is designed to work with desensitized machine data, not intimate access to your sensitive data, because your privacy is very important to us. There's nothing to install on your endpoint or add to your network.
Always Ready And Available
DeepSentry is a high performance programmable security architecture that's always ready and available in the cloud for all of your endpoints. DeepSentry waits for RESTful requests to its 100% cloud-based API to register endpoints, perform training and create reports.

Application-System Data Profiler

Targets Attack Vectors At 50,000 Events Per Second
DeepSentry analyzes the machine data of your software in real-time at the rate of the aggregate read buffer that's 2 MB/sec with read latencies less than tens of milliseconds. It ingests up to 2 million characters of deltas from files per second that's 50,000 events per second on average considering that the average size of a SYSLOG message on an endpoint is only 40 bytes.
DeepSentry ingests data like application logs, service logs, statuses of active processes, network usage statistics, disk usage statistics, web login attempts, actual binary dumps of your software, etc. into an application-system data profiler that performs application-level data profiling and system-level data profiling in real-time to create a complete picture of your endpoints.
Machine data is transformed into fuzzy clusters glued together with logic of modality that determines distribution, commutation, importation, exportation, and isolation — the kind of logic used in root cause analysis time-proven to be effective in incident remediation. It generates relevant contexts and determines past similarities to target possible attack vectors which hackers, exploits and malware, depend on inside your network to launch their attacks.

Get started with a free, no contract 30-day trial to register endpoints, perform training and create reports

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Deep Relational Reinforcement Learning

Determines Relational Bonds Of Fuzzy Clusters With Probability
The machine data you share with DeepSentry can be anything, of any size, of any length — plain text, encrypted text, executable binaries, digital videos, digital images, digital audio — related to software on your endpoint you want DeepSentry to monitor since that machine data teaches DeepSentry how software interacts with entities in your endpoint's environment. The machine data can be application logs, service logs, statuses of active processes, error messages from stop processes, network usage statistics, disk usage statistics, web login attempts, actual binary dumps of your software, etc.
DeepSentry determines with probabilistic confidence and probabilistic credibly the strength/weakness of your software's relational bonds to other entities and to its environment. As the machine data varies in representation the relational bonds of your software will be either strengthened or weakened. Some relational bonds will become stronger, thus will be promoted faster and more frequently. Other relational bonds will become weaker, thus will be reserved for specific uses.
Automatic Learning Of Software Behaviors
DeepSentry automatically learns the seemingly thousands of overlapping events making up software behaviors to determine how you want software to behave on your endpoint. Depending on the complexity of your software, your software may be made up of any number — hundreds of thousands up to hundreds of billions — of relational bonds.

Yields Profound Insights Into What's Really Happening

Game Changing Advantages Over Hackers
Within seconds of unusual activity software like polymorphic malware, metamorphic malware, fileless malware, and zero-day exploits can be prevented from reaching fruition on the endpoint because DeepSentry recognized their malicious interactions with other entities then passed judgement onto the parents/children responsible for requesting the execution of the attack vectors.

Predictive Security Analytics

Calculated Predictions Of Emerging Threats
DeepSentry profiles machine data accumulatively at the rate of data ingestion to create the latest reports. It doesn't save copies of your machine data, it keeps a historical record of the sequences of fuzzy clusters which were created at the time of ingestion.
Predictive Security Analytics include the raw numerical details of relational reinforcement learning used to calculate confidence, credibility, relevance, similarity, logic, etc. Raw numerical details used to predict most likely behaviors. And, an interpretive analysis of endpoint activities and endpoint predictions.