Darktrace

Reduced incidents of data breaches and enhanced response times for cyber threats.

IT Security & Data

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Technology

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Anomaly Detection

Project Overview

Machine learning is used to detect and respond to abnormal behaviors in corporate networks to prevent cyberattacks from both internal and external threats.

Layman's Explanation

Darktrace's AI monitors network activity to recognize "normal" behavior patterns and identify potential threats whenever unusual activity is detected, similar to how an immune system identifies and fights infections.

Analogy

In technology, this is like a vigilant guard dog that learns typical movements in a home and barks at anything suspicious to alert homeowners of potential intrusions.

Details

Darktrace uses machine learning to continually analyze data patterns within a network to establish a baseline of normal activities. This enables it to identify deviations that may indicate security threats, whether from external hackers or internal breaches, and either alert security teams or take automatic countermeasures. Traditional security systems rely on pre-set rules, making them ineffective against novel cyber threats. Darktrace’s system adapts to new patterns, offering real-time protection in rapidly evolving digital environments.

Project Novelty

The adaptive nature of Darktrace’s system is innovative, allowing for real-time adjustments and countermeasures, unlike traditional static rule-based systems.

Project Estimates

Timeline:

8 months

Cost:

$500,000

Headcount:

7

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