Deep-learning based Anomaly Pattern Detection Solution
SME Network Security
Web / log analysis
Analysis / Detection
Applies Deep learning artificial intelligence technology to effectively monitor suspicious behaviors and patterns from internal network as well as identify external threats.
The process is in real-time, and it supports instant update feature to maximize system reliability.
Since buying and running a computing power necessary to implement deep learning can be cost prohibitive, Ellexi offers monthly subscription based services for customers.
Simplified AI deployment process with deep learning-based time-series NORMAL DATA MODELING
Enables a rapid deployment of the solution, saves at least 80% of the time for integration with 50% less cost
Minimized alarm fatigues through Hybrid approach for anomaly detection
Deep Neural Network + HBKS (Augmented Pattern Memory)
Simplified system update process by applying Model Management Framework
Customizable solution since it has been developed not just for a specific domain
Gradually minimize false positive issues with anomaly pattern storage
Assume every data is ‘Normal’, no tagging or labeling necessary
Using technology that is required before applying the applied Neural network model by reinforcement learning, which is being actively researched
No need of experts to generate rules by consulting, therefore minimize time and cost for deployment
Monitoring & Graph
Graphical presentation of monitoring, learning and verification process
Analytic graphic presentation of anomalies
Automatically collects data-set for automated learning
Explaining the reason and the cause of suspicious patterns (Anomalies)