AI Cyber Analyst Evaluating Third-Party Security Alerts
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Solution Overview
Problem
Existing cyber security systems struggle to provide fast-acting, informative, and easily understandable defensive tools to counter sophisticated cyber threats, which often occur quickly and require timely intervention from cyber-security professionals.
Innovation Solution
An Artificial Intelligence (AI) based cyber security system that employs a data structure with multiple tags to create a consistent and expanding model of ongoing cyber incidents, utilizing a cyber incident graph database to render incidents to end-users and evaluate the quality of alerts from third-party security tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional security tools are used to detect and respond to cyber threats, then basic security monitoring can be provided, but the system cannot keep up with the speed and sophistication of modern cyber attacks
Solution Approach 1:
The patent replaces traditional mechanical rule-based security systems with an AI-based neural network system that learns and adapts automatically. The neural network analyzes security events and generates alerts with higher accuracy and speed, substituting the mechanical processing of traditional tools with intelligent, adaptive processing that keeps pace with sophisticated cyber attacks.
2Measurement precision
If AI-based analysis is implemented to improve threat detection accuracy, then detection precision improves, but system complexity increases
Solution Approach 1:
The patent implements a self-training neural network system that automatically learns from security events without requiring manual configuration or extensive expert intervention. The system serves itself by continuously improving its detection capabilities through automated learning from the data it processes, reducing the operational complexity despite the advanced AI technology.
Solution Approach 2:
The patent introduces an AI-based intermediary layer that sits between raw security events and final alerts. This neural network intermediary processes and interprets complex security data, transforming it into actionable insights while managing the complexity internally, thus providing high detection precision without proportionally increasing user-facing system complexity.
3Adaptability or versatility
If multiple security tools are deployed to cover different attack vectors, then detection coverage improves, but false positive rates increase
Solution Approach 1:
The patent merges inputs from multiple security tools and data sources into a unified AI-based analysis system. The neural network processes events from various security tools simultaneously, learning to correlate and contextualize them to distinguish true threats from false positives, thus maintaining comprehensive detection coverage while improving alert fidelity through intelligent synthesis.
Data Source
AI summary
Methods, systems, and apparatus are disclosed for an Artificial Intelligence based cyber security system. An Artificial Intelligence based cyber analyst can make use of a data structure containing multiple tags to assist in creating a consistent, expanding modeling of an ongoing cyber incident. The Artificial Intelligence based cyber analyst can make use of a cyber incident graph database when rendering that incident to an end user. The Artificial Intelligence based cyber analyst can also be used as a mechanism to evaluate the quality of the alerts coming from 3rd parties' security tools both when the system being protected by the cyber security appliance is not actually under attack by a cyber threat as well as during an attack by a cyber threat.