Philo-AD

Deep-learning based Anomaly Pattern Detection Solution

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SME Network Security

Web / log analysis

Anomaly Detection

APT

ESM/IDS/IPS/DRM

Smart Factory

Process Management

Energy management

Quality Analysis

Predictive Maintenance

Finance

FDS

Data Collection

Analysis / Detection

Monitoring

Philo-AD

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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

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Features

Versatile

Customizable solution since it has been developed not just for a specific domain

Precision

Gradually minimize false positive issues with anomaly pattern storage

Convenience

Assume every data is ‘Normal’, no tagging or labeling necessary

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Practical

Using technology that is required before applying the applied Neural network model by reinforcement learning, which is being actively researched

No expert

No need of experts to generate rules by consulting, therefore minimize time and cost for deployment

Dashboard

  • Monitoring & Graph
    Graphical presentation of monitoring, learning and verification process
    Analytic graphic presentation of anomalies

  • Auto Learning
    Automatically collects data-set for automated learning

  • Explainable
    Explaining the reason and the cause of suspicious patterns (Anomalies)

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Case Study

MONITECH

AI-based welding monitoring system for welding quality of EV batteries

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KT RND Center

KT.com Web log Anomaly Pattern Detection System for Netflow

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